Triple
T10887894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidi VanDerveer |
E257095
|
entity |
| Predicate | coachedGender |
P96242
|
FINISHED |
| Object | women |
—
|
LITERAL 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: women | Statement: [Heidi VanDerveer, coachedGender, women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachedGender Context triple: [Heidi VanDerveer, coachedGender, women]
-
A.
coachedFrom
Indicates that one entity served as a coach or trainer for another entity during a specified period or context.
-
B.
coachedAlongside
Indicates that two or more individuals served as coaches at the same time, typically for the same team, organization, or event.
-
C.
playsGender
Indicates that one entity performs or assumes a particular gender role or identity in a given context.
-
D.
coachedFormat
Indicates that one entity served as a coach or trainer to another entity in a particular format, style, or structured context.
-
E.
coachedUntil
Indicates that one entity served as a coach for another entity or team up to a specified end time or date.
- F. None of above. chosen
Provenance (4 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75201e6888190a2bc41a17784eec3 |
completed | April 9, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69d70d3943c881908895397eccc3e415 |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101de31c819090707635f6790559 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:21 p.m.