Triple
T30896541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Safavid Sufi order |
E787035
|
entity |
| Predicate | hadMilitaryFollowing |
P170280
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Safavid Sufi order, hadMilitaryFollowing, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMilitaryFollowing Context triple: [Safavid Sufi order, hadMilitaryFollowing, yes]
-
A.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
B.
hadMilitaryServiceFrom
Indicates that an entity performed or was engaged in military service starting from a specified point in time.
-
C.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
D.
hasMilitaryPost
Indicates that an entity holds or is assigned to a specific military position, role, or station.
-
E.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6923baa1081909407a75d6c22a34f |
completed | May 3, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68c517f308190873c1c7e05a0c6d0 |
completed | May 2, 2026, 11:44 p.m. |
Created at: April 29, 2026, 8:49 p.m.