Triple
T28810131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HWH |
E727488
|
entity |
| Predicate | associatedWithMetroArea |
P108274
|
FINISHED |
| Object | Kolkata metropolitan area |
E295867
|
NE 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: Kolkata metropolitan area | Statement: [HWH, associatedWithMetroArea, Kolkata metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithMetroArea Context triple: [HWH, associatedWithMetroArea, Kolkata metropolitan area]
-
A.
belongsToMetropolitanRegion
chosen
Indicates that one geographic or administrative area is part of, or included within, a larger metropolitan region.
-
B.
metropolitanAreaWith
Indicates that one entity is a metropolitan area that includes, is associated with, or encompasses the other entity.
-
C.
representsMetropolitanArea
Indicates that one entity serves as or corresponds to the metropolitan area associated with another entity.
-
D.
isWithinMetroArea
Indicates that one location lies inside the geographic boundaries of a specified metropolitan area.
-
E.
connectsToMetropolitanAreaInState
Indicates that an entity has a direct connection or linkage to a metropolitan area located within a specified state.
- F. None of above.
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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_6a01d7b3ce8c8190b2f90be730505765 |
completed | May 11, 2026, 1:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a25f0e307e88190a11761a5f81a627d |
completed | June 7, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_6a01d5115a6c8190a6d9f96ec484135a |
completed | May 11, 2026, 1:09 p.m. |
Created at: April 28, 2026, 6:30 a.m.