Triple
T23854029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brown Building |
E592252
|
entity |
| Predicate | fireVictims |
P36783
|
FINISHED |
| Object | garment workers |
—
|
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: garment workers | Statement: [Brown Building, fireVictims, garment workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireVictims Context triple: [Brown Building, fireVictims, garment workers]
-
A.
mainVictims
chosen
Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
-
B.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
C.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
D.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
E.
numberOfAdultVictims
Indicates the count of adult individuals who are victims in the described event or situation.
- 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c98954748190b39e0ac69e5625f9 |
completed | April 29, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:11 p.m.