Triple
T6966796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Macy |
E161509
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Garber |
E574761
|
NE FINISHED |
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: Garber | Statement: [Bill Macy, familyName, Garber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garber Context triple: [Bill Macy, familyName, Garber]
-
A.
Garber
chosen
Garber is a surname most notably associated with Canadian actor and singer Victor Garber, known for his work in film, television, and theater.
-
B.
Gabbs
Gabbs is a small, remote town in central Nevada known historically for its mining activities and desert surroundings.
-
C.
Nevin
Nevin is a surname most notably associated with Phil Nevin, a former Major League Baseball player and manager.
-
D.
Farris
Farris is a surname most notably associated with Christine King Farris, an American educator, author, and the elder sister of Martin Luther King Jr.
-
E.
Egan
Egan is a surname of Irish origin borne by various notable individuals, including the American novelist Jennifer Egan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db121174819098e73e45f6c9cc91 |
completed | March 27, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c758a57b8481908cef7de9b3abf7a3 |
completed | March 28, 2026, 4:27 a.m. |
Created at: March 27, 2026, 2:30 p.m.