Triple
T1535424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Moore |
E32538
|
entity |
| Predicate | WoodenAwardWinnerInSeason |
P13586
|
FINISHED |
| Object | 2008–09 |
—
|
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: 2008–09 | Statement: [Maya Moore, WoodenAwardWinnerInSeason, 2008–09]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WoodenAwardWinnerInSeason Context triple: [Maya Moore, WoodenAwardWinnerInSeason, 2008–09]
-
A.
awardSeason
chosen
Indicates the period or context in which awards are given or recognized for achievements, typically within a specific field or industry.
-
B.
awardMaterial
Indicates that one entity grants or provides a tangible item or resource (a material) to another, typically as a form of recognition or reward.
-
C.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
D.
awardType
Indicates the specific category or kind of award associated with an entity or event.
-
E.
awardName
Indicates the specific name or title of an award associated with an entity.
- F. None of above.
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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a915f323bc8190aa757142c225e0ae |
completed | March 5, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69a907b046448190be8ea4d7b20255f7 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.