Triple
T6958298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple of the Inscriptions |
E161302
|
entity |
| Predicate | hasNumberOfInscribedPanels |
P73765
|
FINISHED |
| Object | three main panels |
—
|
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: three main panels | Statement: [Temple of the Inscriptions, hasNumberOfInscribedPanels, three main panels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfInscribedPanels Context triple: [Temple of the Inscriptions, hasNumberOfInscribedPanels, three main panels]
-
A.
numberOfStainedGlassPanels
Indicates the count of stained glass panels associated with a given entity or object.
-
B.
numberOfPanels
Indicates the total count of distinct panels associated with or contained within a given entity.
-
C.
hasNumberOfVocationalPanels
Indicates the relationship specifying how many vocational panels are associated with a given entity.
-
D.
isInscribedOn
Indicates that text, symbols, or markings are written, carved, or otherwise permanently placed onto the surface of an object.
-
E.
hasNumberOfNamesInscribed
Indicates the quantity of distinct names that are inscribed on a given 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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dad240ac8190808014a5b4920b41 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c0b0a08190b262dfc94992994d |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d9bb57e88190a3a7cec34e3b617f |
completed | March 27, 2026, 7:25 p.m. |
Created at: March 27, 2026, 2:29 p.m.