Triple
T4513008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navadvipa |
E102092
|
entity |
| Predicate | traditionalReputation |
P49855
|
FINISHED |
| Object | seat of learning in Bengal |
—
|
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: seat of learning in Bengal | Statement: [Navadvipa, traditionalReputation, seat of learning in Bengal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalReputation Context triple: [Navadvipa, traditionalReputation, seat of learning in Bengal]
-
A.
reputationBuiltFor
Indicates that one entity has established or developed a reputation specifically for or in relation to another entity.
-
B.
crowdReputation
Indicates the collective opinion or perceived standing of an entity as judged by a group or general audience.
-
C.
laterReputation
Indicates that an entity’s reputation or status at a later time is being referred to in relation to an earlier point or context.
-
D.
trainingReputation
chosen
Indicates the reputation or perceived quality of an entity based on its history and effectiveness in providing training or instruction to others.
-
E.
associatedWithReputation
Indicates a relationship where an entity is linked to, influenced by, or characterized in terms of another entity’s reputation or perceived standing.
- 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_69bd43d6251c81909deecce3e6e9d69c |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5722d8fc81909c5f2d9a38d17a6b |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd5218afb4819087c99e0a1f22e137 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:02 p.m.