Triple
T5836420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mosque of the Three Doors |
E129481
|
entity |
| Predicate | inscriptionFunction |
P16929
|
FINISHED |
| Object | commemorative inscription |
—
|
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: commemorative inscription | Statement: [Mosque of the Three Doors, inscriptionFunction, commemorative inscription]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inscriptionFunction Context triple: [Mosque of the Three Doors, inscriptionFunction, commemorative inscription]
-
A.
inscriptionBy
Indicates that an inscription was created, written, or carved by a particular agent or entity.
-
B.
inscription
Indicates that text has been written, carved, or engraved onto a surface or object.
-
C.
inscriptionFeature
Indicates that one entity bears or contains an inscribed element or marking that is treated as a notable feature in relation to another entity.
-
D.
inscriptionType
chosen
Indicates the specific kind or category of inscription associated with an entity (e.g., dedicatory, funerary, commemorative).
-
E.
inscriptionBody
Indicates that the predicate links an inscription to the textual content or wording that is inscribed.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.