Triple
T2941914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wiley Post |
E79405
|
entity |
| Predicate | eyeInjuryCause |
P14656
|
FINISHED |
| Object | oil-field accident |
—
|
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: oil-field accident | Statement: [Wiley Post, eyeInjuryCause, oil-field accident]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eyeInjuryCause Context triple: [Wiley Post, eyeInjuryCause, oil-field accident]
-
A.
causeOfInjury
chosen
Indicates that one entity is the source or reason that another entity sustained an injury.
-
B.
eyesPutOutBy
Indicates that one entity has caused another entity’s eyes to be damaged or removed, resulting in blindness.
-
C.
eyeCondition
Indicates that an entity has, experiences, or is characterized by a particular condition or disorder affecting the eyes.
-
D.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
E.
eyeAssociation
Indicates a relationship where one entity is associated with, linked to, or characterized by a particular eye or eye-related feature of another 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_69ad8b1089588190b74d9e2505e45762 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9870e5d08190b3b277ba823fe6a1 |
completed | March 8, 2026, 3:40 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:56 p.m.