Triple
T3187057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carmelit |
E66722
|
entity |
| Predicate | sufferedFire |
P27153
|
FINISHED |
| Object | 2017 |
—
|
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: 2017 | Statement: [Carmelit, sufferedFire, 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sufferedFire Context triple: [Carmelit, sufferedFire, 2017]
-
A.
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.
-
B.
burnType
Indicates the specific category or severity of a burn associated with an entity or event.
-
C.
notableFire
chosen
Indicates that a significant or historically important fire event is associated with the subject.
-
D.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
E.
burningSince
Indicates that an object or substance has been continuously burning from a specified starting time up to the present or another reference time.
- 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_69ad8587c1bc8190a2595f2c22ee1001 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e279288190843837751e852c9e |
completed | March 8, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ad9e04290481909092ddfbe6fdaabc |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.