Triple
T25732502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taraknath Temple |
E645279
|
entity |
| Predicate | hasLocalEconomyImpactOn |
P40344
|
FINISHED |
| Object | Tarakeswar |
—
|
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: Tarakeswar | Statement: [Taraknath Temple, hasLocalEconomyImpactOn, Tarakeswar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalEconomyImpactOn Context triple: [Taraknath Temple, hasLocalEconomyImpactOn, Tarakeswar]
-
A.
localEconomyImpact
chosen
Indicates the effect that an action, event, or entity has on the economic conditions, activities, or performance of a specific local area or community.
-
B.
hasLocalImpact
Indicates that an entity produces effects or consequences within a specific local area or community.
-
C.
impactOnEconomy
Indicates the effect or influence that one factor, event, or action has on the state or performance of an economy.
-
D.
partOfLocalEconomy
Indicates that an entity contributes to, participates in, or is integrated within the economic activities of a specific local area or community.
-
E.
economicImpactRegion
Indicates the region or geographic area that experiences or is affected by a particular economic impact.
- 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 21, 2026, 11:18 p.m.