Triple
T26957182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mordecai Brown |
E678938
|
entity |
| Predicate | handInjuryAdditionalCause |
P14656
|
FINISHED |
| Object | subsequent fall that further damaged fingers |
—
|
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: subsequent fall that further damaged fingers | Statement: [Mordecai Brown, handInjuryAdditionalCause, subsequent fall that further damaged fingers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: handInjuryAdditionalCause Context triple: [Mordecai Brown, handInjuryAdditionalCause, subsequent fall that further damaged fingers]
-
A.
causeOfInjury
chosen
Indicates that one entity is the source or reason that another entity sustained an injury.
-
B.
hasPlaceOfInjury
Indicates that an injury occurred at a specific place or location.
-
C.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
D.
handednessAfterInjury
Indicates the dominant hand or handedness a person exhibits following an injury, especially in contrast to their prior handedness.
-
E.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
- 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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f620e8cf6c8190b9ee7b08d42989dd |
completed | May 2, 2026, 4:06 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 6:28 a.m.