Triple
T6001633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sycamores |
E133609
|
entity |
| Predicate | notableCoach |
P550
|
FINISHED |
| Object | Greg Lansing |
E154534
|
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: Greg Lansing | Statement: [Sycamores, notableCoach, Greg Lansing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Lansing Context triple: [Sycamores, notableCoach, Greg Lansing]
-
A.
Greg Lansing
chosen
Greg Lansing is an American college basketball coach best known for his tenure as head coach of the Indiana State Sycamores men's basketball program.
-
B.
Andrew Lesnie
Andrew Lesnie was an Australian cinematographer best known for his Oscar-winning work on Peter Jackson’s The Lord of the Rings film trilogy.
-
C.
John Linson
John Linson is an American film and television producer best known for creating the series Yellowstone and producing projects like Sons of Anarchy.
-
D.
Michael Krieger
Michael Krieger is a fictional character appearing in the story of "Watch Over Me."
-
E.
Neil Hartley
Neil Hartley is a film and television producer known for his work on the adaptation of "The Go-Between."
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee7c0e08190a6e78969448b070a |
completed | March 22, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11365741c819097a43a49dd2428c1 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:05 p.m.