Triple
T26725993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trisastisalakapurusacaritra |
E673837
|
entity |
| Predicate | numberOfFiguresDescribed |
P6685
|
FINISHED |
| Object | 63 |
—
|
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: 63 | Statement: [Trisastisalakapurusacaritra, numberOfFiguresDescribed, 63]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFiguresDescribed Context triple: [Trisastisalakapurusacaritra, numberOfFiguresDescribed, 63]
-
A.
numberOfFiguresDepicted
chosen
Indicates the total count of distinct figures shown within a given depiction or representation.
-
B.
numberOfIllustrations
Indicates the quantity of illustrations associated with or contained in an entity.
-
C.
numberDescribedAs
Indicates that a number is characterized, labeled, or referred to using a particular description or phrase.
-
D.
numberOfBronzeFigures
Indicates the quantity of bronze figures associated with a given subject or context.
-
E.
numberOfAvatarsDescribed
Indicates the count of distinct avatars that are described in a given context or data record.
- 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fe0d165a48819098b854318a50d76c |
completed | May 8, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69fe0931002481908a95b34f95e9f64e |
completed | May 8, 2026, 4:02 p.m. |
Created at: April 27, 2026, 3:42 a.m.