Triple
T31155119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeanette Juanita Ward |
E794181
|
entity |
| Predicate | spouseCharacterPlayed |
P192842
|
FINISHED |
| Object |
Paul Drake
Paul Drake is a fictional private detective best known as Perry Mason’s resourceful investigator in Erle Stanley Gardner’s novels and their television adaptations.
|
E137612
|
NE FINISHED |
How this triple was built (3 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: Paul Drake | Statement: [Jeanette Juanita Ward, spouseCharacterPlayed, Paul Drake]
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: Paul Drake Triple: [Jeanette Juanita Ward, spouseCharacterPlayed, Paul Drake]
Generated description
Paul Drake is a fictional private detective best known as Perry Mason’s resourceful investigator in Erle Stanley Gardner’s novels and their television adaptations.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseCharacterPlayed Context triple: [Jeanette Juanita Ward, spouseCharacterPlayed, Paul Drake]
-
A.
spouseCharacterOf
Indicates a marital relationship where one character is the spouse of another character.
-
B.
portrayedBySpouseOf
Indicates that something is portrayed or depicted by the spouse of a given entity.
-
C.
spouseOfRole
Indicates that one role is the spouse (husband, wife, or equivalent marital partner) of another role.
-
D.
spouseAppearsIn
Indicates that the spouse of a given person appears or is featured in a specified work, context, or setting.
-
E.
hasSpouseInTVSeries
Indicates that one person is the spouse of another person within the context of a specific TV series.
- F. None of above. chosen
Provenance (7 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a294724a63c81908c3b698ae7bbbeed |
completed | June 10, 2026, 11:14 a.m. |
| NEDg | Description generation | batch_6a294edf1d4c8190adf74910b3e043a3 |
completed | June 10, 2026, 11:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a294f6bb52c8190a5dd68fdcab3c805 |
completed | June 10, 2026, 11:50 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
| PDg | Predicate description generation | batch_69fd2cf29f808190856ab1d43a51d5c7 |
completed | May 8, 2026, 12:23 a.m. |
Created at: April 29, 2026, 9:06 p.m.