Triple
T12781037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bhutto family |
E305505
|
entity |
| Predicate | hasTragicEvents |
P22468
|
FINISHED |
| Object | assassination of Zulfikar Ali Bhutto |
—
|
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: assassination of Zulfikar Ali Bhutto | Statement: [Bhutto family, hasTragicEvents, assassination of Zulfikar Ali Bhutto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTragicEvents Context triple: [Bhutto family, hasTragicEvents, assassination of Zulfikar Ali Bhutto]
-
A.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
-
B.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
C.
hadEvent
chosen
Indicates that an entity experienced, hosted, or was associated with a specific event at some point in time.
-
D.
hasTragicEnding
Indicates that the event, story, or situation concludes with a sorrowful, disastrous, or otherwise deeply unfortunate outcome.
-
E.
otherMajorTragedy
Indicates that the subject experienced or was involved in a significant tragic event other than the primary or most notable tragedy under consideration.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5a5680819095dcd491486d23e7 |
completed | April 10, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:29 p.m.