Triple
T18675917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Coke |
E456601
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Thomas |
—
|
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 | Statement: [Thomas Coke, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas Coke, givenName, Thomas]
-
A.
Thomas
Thomas is the given name of Sir Stamford Raffles, the British statesman best known as the founder of modern Singapore.
-
B.
Thomas
Thomas is the middle name of the individual Samuel Thomas Wilson.
-
C.
Thomas
chosen
Thomas is the given name of Thomas Coke, 2nd Earl of Leicester, a prominent 19th-century British peer and landowner.
-
D.
Thomas
Thomas is the full given name of former NFL quarterback Tommy Maddox, who notably played for the Pittsburgh Steelers and won the 2001 XFL championship.
-
E.
Thomas
Thomas is a character appearing in the animated series "Exit 9B" from the show "Regular Show."
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b5a52c81908a71ac86544fb6aa |
completed | April 19, 2026, 10:27 p.m. |
Created at: April 10, 2026, 11:48 a.m.