Triple
T20017317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monte Pearce |
E494755
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Monte
Monte is a masculine given name, often used in English-speaking countries, that can be a standalone name or a diminutive of names like Montgomery.
|
E1407123
|
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: Monte | Statement: [Monte Pearce, givenName, Monte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monte Context triple: [Monte Pearce, givenName, Monte]
-
A.
Monte
Monte is the costumed grizzly bear mascot who represents the University of Montana at athletic events and campus activities.
-
B.
Monte
Monte was the nickname of Monte Irvin, a Hall of Fame American baseball player renowned as one of the early Black stars to break Major League Baseball’s color barrier.
-
C.
Monte
Monte is a burial site associated with Charles IV, likely a historically significant location connected to his death and interment.
-
D.
Monte Frank
Monte Frank is a Connecticut attorney and civic leader who ran for governor as a third-party candidate in the 2018 Connecticut gubernatorial election.
-
E.
The Mount
The Mount is the English name for Surah At-Tur, a chapter of the Qur’an that emphasizes God’s power, the reality of resurrection, and the fate of believers and disbelievers.
- 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: Monte Triple: [Monte Pearce, givenName, Monte]
Generated description
Monte is a masculine given name, often used in English-speaking countries, that can be a standalone name or a diminutive of names like Montgomery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Monte Target entity description: Monte is a masculine given name, often used in English-speaking countries, that can be a standalone name or a diminutive of names like Montgomery.
-
A.
Monte
Monte was the nickname of Monte Irvin, a Hall of Fame American baseball player renowned as one of the early Black stars to break Major League Baseball’s color barrier.
-
B.
Monte
Monte is the costumed grizzly bear mascot who represents the University of Montana at athletic events and campus activities.
-
C.
Monte
Monte is a burial site associated with Charles IV, likely a historically significant location connected to his death and interment.
-
D.
Monte Frank
Monte Frank is a Connecticut attorney and civic leader who ran for governor as a third-party candidate in the 2018 Connecticut gubernatorial election.
-
E.
The Mount
The Mount is the English name for Surah At-Tur, a chapter of the Qur’an that emphasizes God’s power, the reality of resurrection, and the fate of believers and disbelievers.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623d76808190988990a8dc263ef7 |
completed | April 20, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a080e25511081909f4bd039531c30ec |
completed | May 16, 2026, 6:26 a.m. |
| NEDg | Description generation | batch_6a080f164ed88190be61cb4637b2c626 |
completed | May 16, 2026, 6:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a080f8bb81c819098d39ad6e1642aa8 |
completed | May 16, 2026, 6:32 a.m. |
Created at: April 11, 2026, 3:34 p.m.