Triple
T29384836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sufa crossing |
E745222
|
entity |
| Predicate | nearbyConflictZone |
P21190
|
FINISHED |
| Object | Gaza Strip |
—
|
NE NERFINISHED |
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: Gaza Strip | Statement: [Sufa crossing, nearbyConflictZone, Gaza Strip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyConflictZone Context triple: [Sufa crossing, nearbyConflictZone, Gaza Strip]
-
A.
nearbyCrashConflictContext
Indicates a contextual relationship where a crash event occurs in close spatial or temporal proximity to another relevant element, creating a potential conflict or interaction between them.
-
B.
locatedOnSideOfConflict
Indicates that an entity is positioned or aligned on a particular side or faction within a conflict.
-
C.
nearbyBattlefield
Indicates that one entity is located close to or in the immediate vicinity of a battlefield.
-
D.
conflictRegion
chosen
Indicates that the entities are located in or associated with a geographic area characterized by active or recent conflict, tension, or hostilities.
-
E.
factionZoneFor
Indicates that a specific area or zone is designated as belonging to, controlled by, or associated with a particular faction.
- 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 28, 2026, 2:38 p.m.