Triple
T33767790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muslim ibn Aqil |
E865283
|
entity |
| Predicate | governorOpposedInKufa |
P202749
|
FINISHED |
| Object | Ubayd Allah ibn Ziyad |
—
|
NE NERFINISHED |
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: Ubayd Allah ibn Ziyad | Statement: [Muslim ibn Aqil, governorOpposedInKufa, Ubayd Allah ibn Ziyad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governorOpposedInKufa Context triple: [Muslim ibn Aqil, governorOpposedInKufa, Ubayd Allah ibn Ziyad]
-
A.
coupLeaderOpposedBy
Indicates that the identified coup leader is actively resisted, challenged, or opposed by another specified party.
-
B.
notableLeaderOpposed
Indicates that a prominent or influential leader actively resisted, disagreed with, or worked against the referenced person, group, policy, or cause.
-
C.
opposedByLeader
Indicates that an action, proposal, or position is actively resisted or rejected by a leader.
-
D.
opponentInKhartoum
Indicates that one entity is an opponent of another in the context of Khartoum (e.g., in a conflict, competition, or political struggle located there).
-
E.
sideInBattleOfSiffin
Indicates that an entity was aligned with or fought on a particular side during the Battle of Siffin.
- 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_69f3498d3b748190aa3c4006c1f32f38 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00b3d2e0c88190a8bf49576e654f64 |
completed | May 10, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_6a00b376f4e48190a6676779fe02ea9f |
completed | May 10, 2026, 4:33 p.m. |
| PDg | Predicate description generation | batch_6a00b3d23bdc8190b45dd7eefa72ead5 |
completed | May 10, 2026, 4:35 p.m. |
Created at: May 1, 2026, 1:45 a.m.