Triple
T26725233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svetambara canon |
E673818
|
entity |
| Predicate | hasNumberOfAngas |
P180126
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Svetambara canon, hasNumberOfAngas, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfAngas Context triple: [Svetambara canon, hasNumberOfAngas, 11]
-
A.
hasNumberOfPrakaras
Indicates the relationship specifying how many prakaras (enclosure layers or surrounding structures) are associated with a given entity.
-
B.
hasPādaCount
Indicates the relationship specifying how many pādas (metrical feet or lines) are associated with a given entity.
-
C.
hasArmCount
Indicates the number of arms that an entity possesses.
-
D.
hasNumberOfWuku
Indicates the relationship that specifies how many wuku (traditional Javanese calendar weeks) are associated with a given entity.
-
E.
hasNumberOfKandas
Indicates the relationship specifying how many kandas (sections or books) are associated with 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
| PDg | Predicate description generation | batch_69f73221eef88190bd8905e6e9f5a586 |
completed | May 3, 2026, 11:31 a.m. |
Created at: April 27, 2026, 3:42 a.m.