Triple
T27429123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarah Jean Collins |
E690576
|
entity |
| Predicate | hasNotableInjury |
P3816
|
FINISHED |
| Object | injuries from church bombing |
—
|
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: injuries from church bombing | Statement: [Sarah Jean Collins, hasNotableInjury, injuries from church bombing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableInjury Context triple: [Sarah Jean Collins, hasNotableInjury, injuries from church bombing]
-
A.
hasInjuries
chosen
Indicates that an entity has sustained one or more physical or bodily injuries.
-
B.
injuryStatus
Indicates the condition or state of harm, damage, or physical injury affecting an entity.
-
C.
hasPlaceOfInjury
Indicates that an injury occurred at a specific place or location.
-
D.
hasNotableIncident
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
-
E.
hasInjuredPerson
Indicates that an entity has a person who has been harmed or injured associated with it.
- 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_69ef52003fb48190b0f1295246182a86 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fe7bfc94bc81909eeec946e8c1c450 |
completed | May 9, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69fe7b74a1188190886f128e07f712da |
completed | May 9, 2026, 12:10 a.m. |
Created at: April 27, 2026, 12:41 p.m.