Triple
T9279292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam Beesly |
E223028
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Philip Halpert
Philip Halpert is the infant son of Jim Halpert and Pam Beesly on the U.S. television series "The Office."
|
E788051
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Philip Halpert | Statement: [Pam Beesly, hasChild, Philip Halpert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philip Halpert Context triple: [Pam Beesly, hasChild, Philip Halpert]
-
A.
Pete Garvey
Pete Garvey is the charming, fast-talking bachelor portrayed by Bing Crosby in the 1951 musical comedy film "Here Comes the Groom."
-
B.
Felix Unger
Felix Unger is an Austrian cardiac surgeon and academic known for co-founding and leading the European Academy of Sciences and Arts.
-
C.
Felix Unger
Felix Unger is a fictional, fastidious and neurotic neat-freak character best known as one of the mismatched roommates in Neil Simon’s play and subsequent adaptations of "The Odd Couple."
-
D.
Jerry Mulligan
Jerry Mulligan is the charismatic American ex-GI and aspiring painter living in postwar Paris who serves as the romantic lead in the musical film "An American in Paris."
-
E.
Nathaniel Blume
Nathaniel Blume is a contemporary American composer best known for his work on television and film scores, particularly in the crime and thriller genres.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Philip Halpert Triple: [Pam Beesly, hasChild, Philip Halpert]
Generated description
Philip Halpert is the infant son of Jim Halpert and Pam Beesly on the U.S. television series "The Office."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Philip Halpert Target entity description: Philip Halpert is the infant son of Jim Halpert and Pam Beesly on the U.S. television series "The Office."
-
A.
Pete Garvey
Pete Garvey is the charming, fast-talking bachelor portrayed by Bing Crosby in the 1951 musical comedy film "Here Comes the Groom."
-
B.
Felix Unger
Felix Unger is an Austrian cardiac surgeon and academic known for co-founding and leading the European Academy of Sciences and Arts.
-
C.
Felix Unger
Felix Unger is a fictional, fastidious and neurotic neat-freak character best known as one of the mismatched roommates in Neil Simon’s play and subsequent adaptations of "The Odd Couple."
-
D.
Jerry Mulligan
Jerry Mulligan is the charismatic American ex-GI and aspiring painter living in postwar Paris who serves as the romantic lead in the musical film "An American in Paris."
-
E.
Nathaniel Blume
Nathaniel Blume is a contemporary American composer best known for his work on television and film scores, particularly in the crime and thriller genres.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca842123588190b3f2e1a69037d141 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd07cc79508190954defbef0d82a64 |
completed | April 1, 2026, 11:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09c4f254c819083301449c3e4b11d |
completed | April 4, 2026, 5:06 a.m. |
| NEDg | Description generation | batch_69d09da280288190b40f145e1836a53f |
completed | April 4, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d09df7c7f48190b36b63227ff539b5 |
completed | April 4, 2026, 5:13 a.m. |
Created at: March 30, 2026, 7:34 p.m.