Triple
T3525607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beit Hanoun |
E74530
|
entity |
| Predicate | hasConflictRelatedDamage |
P49265
|
FINISHED |
| Object | residential buildings |
—
|
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: residential buildings | Statement: [Beit Hanoun, hasConflictRelatedDamage, residential buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConflictRelatedDamage Context triple: [Beit Hanoun, hasConflictRelatedDamage, residential buildings]
-
A.
hasDam
Indicates that a watercourse, reservoir, or similar feature is impounded or controlled by a specific dam.
-
B.
coversDamageType
Indicates that one entity provides protection, compensation, or applicability for a specified type of damage.
-
C.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
D.
hasPartOfConflict
Indicates that one conflict includes another conflict as a constituent or subordinate part of it.
-
E.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6a8d0c819094d38b9c47fb67b4 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae121a048190b03825a001d21f49 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:19 p.m.