Triple
T36608166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blackwater USA |
E903092
|
entity |
| Predicate | numberOfCivilianDeathsAtNisourSquare |
P34802
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [Blackwater USA, numberOfCivilianDeathsAtNisourSquare, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCivilianDeathsAtNisourSquare Context triple: [Blackwater USA, numberOfCivilianDeathsAtNisourSquare, 17]
-
A.
numberOfCiviliansInjured
Indicates the count of civilian individuals who were injured as a result of a specific event or action.
-
B.
casualtiesCiviliansKilled
chosen
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
-
C.
deathInTerroristAttack
Indicates that an entity died as a direct result of a terrorist attack.
-
D.
numberOfPeopleInjuredInBombings
Indicates the count of individuals who were injured as a result of bombing incidents.
-
E.
numberOfPeopleKilledInBombing
Indicates the total count of people who were killed as a direct result of a specific bombing event.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.