Triple
T23853825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triangle Waist Company |
E592247
|
entity |
| Predicate | numberOfDeathsInFire |
P63692
|
FINISHED |
| Object | 146 |
—
|
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: 146 | Statement: [Triangle Waist Company, numberOfDeathsInFire, 146]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDeathsInFire Context triple: [Triangle Waist Company, numberOfDeathsInFire, 146]
-
A.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
B.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
C.
firefighterFatalities
Indicates that the situation or event involves deaths of firefighters in the line of duty or as a result of firefighting-related activities.
-
D.
numberOfVictimsKilled
chosen
Indicates the count of victims who were killed as a result of the referenced event or action.
-
E.
numberOfPeopleReportedKilled
Indicates the reported count of people who have been killed in an incident or event.
- 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.