Triple
T27931538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badlapur |
E707993
|
entity |
| Predicate | distanceFromThaneApprox |
P200682
|
FINISHED |
| Object | about 35–40 km by rail |
—
|
LITERAL 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: about 35–40 km by rail | Statement: [Badlapur, distanceFromThaneApprox, about 35–40 km by rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromThaneApprox Context triple: [Badlapur, distanceFromThaneApprox, about 35–40 km by rail]
-
A.
distanceFromPune
Indicates the spatial distance between a given location or entity and the city of Pune.
-
B.
distanceFromNashik
Indicates the spatial distance between a given entity or location and the city of Nashik.
-
C.
distanceFromAhmednagar
Indicates the spatial distance between a given location or entity and Ahmednagar.
-
D.
distanceFromGhaziabad
Indicates the measured or specified distance separating a given entity or location from Ghaziabad.
-
E.
distanceFromGurugram_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Gurugram.
- F. None of above. chosen
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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69ffa15d53208190ab8574d6c7913e18 |
completed | May 9, 2026, 9:04 p.m. |
| PD | Predicate disambiguation | batch_69ff9eee681c81909434e79c627cb528 |
completed | May 9, 2026, 8:54 p.m. |
| PDg | Predicate description generation | batch_69ffa15c3f348190a59403bc72ac9ed4 |
completed | May 9, 2026, 9:04 p.m. |
Created at: April 27, 2026, 7:03 p.m.