Triple
T37589358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trombay |
E935215
|
entity |
| Predicate | hasResidentialColony |
P9064
|
FINISHED |
| Object | Anushakti Nagar (for BARC employees) |
E403518
|
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: Anushakti Nagar (for BARC employees) | Statement: [Trombay, hasResidentialColony, Anushakti Nagar (for BARC employees)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResidentialColony Context triple: [Trombay, hasResidentialColony, Anushakti Nagar (for BARC employees)]
-
A.
hasResidentialBuilding
Indicates that an entity possesses, contains, or is associated with a residential building as part of its properties or components.
-
B.
hasNearbyColony
Indicates that one entity has another entity located close enough to be considered a nearby colony.
-
C.
hasResidentialArea
chosen
Indicates that an entity includes, contains, or is associated with an area designated for people to live or reside.
-
D.
hasColonialTown
Indicates that one entity possesses, contains, or is associated with a town established or characterized as a colonial settlement.
-
E.
hasColonialCenter
Indicates that one entity serves as the colonial administrative or control center for another entity.
- 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_69f76ece61dc8190a0ab33f8d87d0a7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a40a7fba3608190a7121d9a81443038 |
completed | June 28, 2026, 4:50 a.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:18 p.m.