Triple
T34193951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sangareddy |
E877185
|
entity |
| Predicate | hasNearbyIndustrialHub |
P20649
|
FINISHED |
| Object | Patancheru |
—
|
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: Patancheru | Statement: [Sangareddy, hasNearbyIndustrialHub, Patancheru]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIndustrialHub Context triple: [Sangareddy, hasNearbyIndustrialHub, Patancheru]
-
A.
hasNearbyIndustry
chosen
Indicates that an entity is located close to one or more industrial facilities or activities.
-
B.
connectsToIndustrialArea
Indicates that one entity has a direct link, route, or access connection to an industrial area.
-
C.
nearIndustrialComplex
Indicates that one entity is located in close proximity to an industrial complex.
-
D.
hasNearbyProductionArea
Indicates that one entity has a production area located in close physical proximity to it.
-
E.
hasIndustrialZoneAlong
Indicates that an industrial zone is located adjacent to or extending along the length of a specified linear feature (such as a road, river, or boundary).
- 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffb1218cb08190a814c7f0833501a7 |
completed | May 9, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69ffb083d6988190b2757e0cfd629b75 |
completed | May 9, 2026, 10:09 p.m. |
Created at: May 1, 2026, 1:55 a.m.