Triple
T26533376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amar Akbar Anthony |
E670877
|
entity |
| Predicate | hasReligiousRepresentation |
P195487
|
FINISHED |
| Object | Hinduism |
—
|
NE NERFINISHED |
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: Hinduism | Statement: [Amar Akbar Anthony, hasReligiousRepresentation, Hinduism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousRepresentation Context triple: [Amar Akbar Anthony, hasReligiousRepresentation, Hinduism]
-
A.
hasReligious
Indicates that an entity is associated with, practices, or adheres to a particular religion or religious affiliation.
-
B.
hasReligiousSee
Indicates that one entity serves as the ecclesiastical or religious jurisdiction/seat (see) of another entity.
-
C.
hasReligiousType
Indicates that an entity is associated with or classified under a particular religion or religious category.
-
D.
hasReligiousSignificanceVia
Indicates that something holds religious significance specifically by means of, or through the mediation of, another entity, event, or context.
-
E.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
| PDg | Predicate description generation | batch_69fdd5faea908190a17d77e050362ef5 |
completed | May 8, 2026, 12:24 p.m. |
Created at: April 27, 2026, 1:37 a.m.