Triple
T38424115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PNP Wounded Personnel Medal |
E903311
|
entity |
| Predicate | typeOfInjuryRecognized |
P23450
|
FINISHED |
| Object | wounds sustained during official police operations |
—
|
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: wounds sustained during official police operations | Statement: [PNP Wounded Personnel Medal, typeOfInjuryRecognized, wounds sustained during official police operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfInjuryRecognized Context triple: [PNP Wounded Personnel Medal, typeOfInjuryRecognized, wounds sustained during official police operations]
-
A.
injuryType
chosen
Indicates the specific kind or category of injury associated with an entity or event.
-
B.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
C.
injuryStatus
Indicates the condition or state of harm, damage, or physical injury affecting an entity.
-
D.
injuriesApprox
Indicates an approximate or estimated number or extent of injuries associated with an event or entity.
-
E.
hasPlaceOfInjury
Indicates that an injury occurred at a specific place or location.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.