Triple
T18809327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Meehan |
E459965
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Thomas Meehan |
—
|
NE NERFINISHED |
How this triple was built (2 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: Thomas Meehan | Statement: [Thomas Meehan, name, Thomas Meehan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Meehan Context triple: [Thomas Meehan, name, Thomas Meehan]
-
A.
Thomas Meehan
chosen
Thomas Meehan was an American playwright and librettist best known for writing the books for hit Broadway musicals such as Annie, The Producers, and Hairspray.
-
B.
Marty Meehan
Marty Meehan is an American academic administrator and former U.S. congressman who serves as president of the University of Massachusetts system.
-
C.
Kevin J. Leahy
Kevin J. Leahy is a scholar and author, best known for his work in archaeology and the study of early medieval metalwork in Britain.
-
D.
John Meehan
John Meehan is the real-life conman and serial predator whose story inspired the podcast and TV series "Dirty John," in which he is portrayed by Eric Bana.
-
E.
John Meehan
John Meehan was an American screenwriter known for his work on early- to mid-20th-century Hollywood films, including notable dramas and comedies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d9c49c8190a9d29a25f0c977b2 |
completed | April 20, 2026, 3:56 a.m. |
Created at: April 10, 2026, 11:53 a.m.