Triple
T10095146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1977 New York City blackout-related unrest |
E215845
|
entity |
| Predicate | hasTypeOfDamage |
P92407
|
FINISHED |
| Object | commercial property damage |
—
|
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: commercial property damage | Statement: [1977 New York City blackout-related unrest, hasTypeOfDamage, commercial property damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfDamage Context triple: [1977 New York City blackout-related unrest, hasTypeOfDamage, commercial property damage]
-
A.
sufferedDamageTo
Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
-
B.
hasDam
Indicates that a watercourse, reservoir, or similar feature is impounded or controlled by a specific dam.
-
C.
coversDamageType
Indicates that one entity provides protection, compensation, or applicability for a specified type of damage.
-
D.
hasConflictRelatedDamage
Indicates that an entity has incurred damage that is directly related to, or caused by, a conflict or conflict-related event.
-
E.
damagedIn
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
- 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd0784c288190967d143beca32c4b |
completed | April 2, 2026, 2:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9b853c8190a2af993ce9b21309 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd5150ae98819086c4f822114b4e2c |
completed | April 1, 2026, 5:09 p.m. |
Created at: March 30, 2026, 9:02 p.m.