Triple
T12217039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Monroe Trotter |
E291111
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Trotter |
E332380
|
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: Trotter | Statement: [William Monroe Trotter, familyName, Trotter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trotter Context triple: [William Monroe Trotter, familyName, Trotter]
-
A.
Trotter
chosen
Trotter is the surname of Tariq "Black Thought" Trotter, the acclaimed rapper, lead MC of The Roots, and influential figure in hip-hop.
-
B.
Trott
Trott is a surname of English origin borne by various notable individuals across fields such as law, sports, and the arts.
-
C.
Ottis
Ottis is a masculine given name most notably borne by former NFL running back Ottis Anderson.
-
D.
Tucker
Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
-
E.
Tucker
Tucker is a paranormal investigator character from the Insidious horror film series, known for his tech-based ghost-hunting work alongside his partner Specs.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c9419d48190b0037fe8edc681c4 |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa31f548190bd4f8cfe3c55614b |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:51 p.m.