Triple
T36044721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muş Castle |
E1042636
|
entity |
| Predicate | hasRemnantsFrom |
P16216
|
FINISHED |
| Object | ancient period |
—
|
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: ancient period | Statement: [Muş Castle, hasRemnantsFrom, ancient period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRemnantsFrom Context triple: [Muş Castle, hasRemnantsFrom, ancient period]
-
A.
hasRemainsOf
chosen
Indicates that one entity physically contains, preserves, or is associated with the leftover physical traces or remnants of another entity.
-
B.
remnantUsedBy
Indicates that a remaining part or leftover of something is utilized or employed by another entity.
-
C.
remnantsInclude
Indicates that the remaining parts or leftovers of one entity contain or consist of another entity.
-
D.
hasStructureRemnant
Indicates that an entity contains or includes a remaining part or leftover portion of a former structure.
-
E.
remnants
Indicates that parts or traces of something remain after the main portion has been removed, used, or destroyed.
- 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_69f76e2e41f8819091f9fb0536920fec |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.