Triple
T1988317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiswah |
E43190
|
entity |
| Predicate | earlierVersionsSponsoredBy |
P35197
|
FINISHED |
| Object | Muslim caliphs |
—
|
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: Muslim caliphs | Statement: [Kiswah, earlierVersionsSponsoredBy, Muslim caliphs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earlierVersionsSponsoredBy Context triple: [Kiswah, earlierVersionsSponsoredBy, Muslim caliphs]
-
A.
formerSponsor
Indicates that an entity previously acted as a sponsor for another entity but no longer holds that sponsoring role.
-
B.
previousSponsor
Indicates that an entity formerly acted as a sponsor for another entity at some earlier time but no longer does so.
-
C.
previouslySupported
Indicates that an entity provided support to another entity at some time in the past, but not necessarily in the present.
-
D.
previousSponsorshipName
Indicates that an entity had a different sponsorship name in the past, specifying what that prior sponsored name was.
-
E.
previousVersionAdopted
Indicates that one entity has been adopted or implemented as a successor to an earlier version represented by the other entity.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69abb8ec608c81908917e945e0118ac4 |
completed | March 7, 2026, 5:34 a.m. |
Created at: March 4, 2026, 7:37 p.m.