Triple
T2244162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edwin Moses |
E49463
|
entity |
| Predicate | genreOfSport |
P24022
|
FINISHED |
| Object | hurdling |
—
|
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: hurdling | Statement: [Edwin Moses, genreOfSport, hurdling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfSport Context triple: [Edwin Moses, genreOfSport, hurdling]
-
A.
sportEventType
Indicates the specific kind or category of sport associated with a given sporting event.
-
B.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
-
C.
sportGender
Indicates that a sport or sporting event is associated with a particular gender category (e.g., men's, women's, mixed).
-
D.
sportsName
chosen
Indicates the specific sport associated with or played in a given context or event.
-
E.
originalSport
Indicates that one sport is the initial or primary sport associated with an entity, often before any change, adaptation, or transition to another sport.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0c157e88190a5bc876d9591a24b |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.