Triple
T33280751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 Los Angeles riots |
E852035
|
entity |
| Predicate | numberOfFires |
P203999
|
FINISHED |
| Object | over 1000 |
—
|
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: over 1000 | Statement: [1992 Los Angeles riots, numberOfFires, over 1000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFires Context triple: [1992 Los Angeles riots, numberOfFires, over 1000]
-
A.
numberOfFirefightersInvolved
Indicates the total count of firefighters who participated in or were involved in a specific event, incident, or operation.
-
B.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
-
C.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
D.
fireOccurred
Indicates that a fire event took place at a specific time and/or location.
-
E.
fires
Indicates that an agent initiates the discharge or ignition of something, such as a weapon, engine, or explosive device, causing it to operate or go off.
- F. None of above. chosen
Provenance (4 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_69f349653da08190819876015a298fdb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0308a4591081909018e2ba5d70096e |
completed | May 12, 2026, 11:01 a.m. |
| PD | Predicate disambiguation | batch_6a03079299708190a2ecaf14d3f06f48 |
completed | May 12, 2026, 10:57 a.m. |
| PDg | Predicate description generation | batch_6a0308a3b03c8190b7fc9553afe06cb5 |
completed | May 12, 2026, 11:01 a.m. |
Created at: May 1, 2026, 1:32 a.m.