Triple
T30745299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bábí movement |
E782800
|
entity |
| Predicate | hadArmedConflictsAt |
P13112
|
FINISHED |
| Object | Shaykh Tabarsí |
—
|
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: Shaykh Tabarsí | Statement: [Bábí movement, hadArmedConflictsAt, Shaykh Tabarsí]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadArmedConflictsAt Context triple: [Bábí movement, hadArmedConflictsAt, Shaykh Tabarsí]
-
A.
hasHistoricalPeriodOfConflict
Indicates that there exists a specific historical period during which the related entities were engaged in conflict or hostilities.
-
B.
militaryConflictIn
Indicates that a military conflict takes place within, or is geographically located in, a specified area or region.
-
C.
warParticipatedIn
chosen
Indicates that an entity took part as a combatant or active participant in a specific war or armed conflict.
-
D.
conflictExperience
Indicates that an entity has undergone or been involved in a conflict, such as a dispute, struggle, or confrontation.
-
E.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
- 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_69f224aeb1588190897d395e8ed2acb8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68f6cba0c8190a02288899be05007 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:38 p.m.