Triple
T21242973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teddy Duchamp |
E523523
|
entity |
| Predicate | physicalInjury |
P71097
|
FINISHED |
| Object | burned ears |
—
|
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: burned ears | Statement: [Teddy Duchamp, physicalInjury, burned ears]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: physicalInjury Context triple: [Teddy Duchamp, physicalInjury, burned ears]
-
A.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
-
B.
involvedPhysicalEffect
Indicates that one entity participates in causing, experiencing, or mediating a physical effect on another entity or the environment.
-
C.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
D.
injuredBodyPart
chosen
Indicates that an entity has sustained an injury specifically affecting a particular body part.
-
E.
injuriesApprox
Indicates an approximate or estimated number or extent of injuries associated with an event or 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7352507448190ba1f14cef16d69be |
completed | April 21, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:47 p.m.