Triple
T29362501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timarpur |
E744627
|
entity |
| Predicate | hasNearbyGovernmentArea |
P72400
|
FINISHED |
| Object | Delhi Vidhan Sabha area |
—
|
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: Delhi Vidhan Sabha area | Statement: [Timarpur, hasNearbyGovernmentArea, Delhi Vidhan Sabha area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyGovernmentArea Context triple: [Timarpur, hasNearbyGovernmentArea, Delhi Vidhan Sabha area]
-
A.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
B.
nearbyPoliticalEntity
Indicates that one political entity is geographically close to another political entity, without necessarily sharing a border.
-
C.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
-
D.
locatedNearGovernmentDistrict
chosen
Indicates that one entity is situated close to or in the immediate vicinity of a government district.
-
E.
governingBodyNearby
Indicates that a governing body is located in close physical proximity to the referenced entity or area.
- 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_69f0a79aee588190b490f19d93c6e52d |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: April 28, 2026, 2:19 p.m.