Triple
T32845308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black September |
E840082
|
entity |
| Predicate | killedInMunichAttack |
P153760
|
FINISHED |
| Object | 11 Israeli athletes and coaches |
—
|
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: 11 Israeli athletes and coaches | Statement: [Black September, killedInMunichAttack, 11 Israeli athletes and coaches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: killedInMunichAttack Context triple: [Black September, killedInMunichAttack, 11 Israeli athletes and coaches]
-
A.
MunichMassacreVictims
Indicates that the entities are victims of the Munich massacre attack.
-
B.
deathInTerroristAttack
Indicates that an entity died as a direct result of a terrorist attack.
-
C.
killedInAttack
chosen
Indicates that an entity died as a direct result of a specific attack event.
-
D.
martyredUnder
Indicates that an entity was killed or executed as a martyr during the rule, authority, or actions of another entity.
-
E.
massacreOccurredIn
Indicates that a massacre took place within the specified location or area.
- 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_69f3493ff0888190b51e974eae2a7834 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6ce6d659881909ddcec1d2966e020 |
completed | May 3, 2026, 4:26 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1667a48190b42684f6ec22dae9 |
completed | May 3, 2026, 4:16 a.m. |
Created at: May 1, 2026, 1:16 a.m.