Triple
T19548339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Firozabad |
E489132
|
entity |
| Predicate | distanceToNewDelhi_km |
P42970
|
FINISHED |
| Object | about 250 |
—
|
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 250 | Statement: [Firozabad, distanceToNewDelhi_km, about 250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNewDelhi_km Context triple: [Firozabad, distanceToNewDelhi_km, about 250]
-
A.
distanceToDelhiApproxKm
chosen
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Delhi.
-
B.
distanceToDelhiByRoad_km
Indicates the road travel distance, measured in kilometers, from a given place to Delhi.
-
C.
distanceToDelhiByRail_km
Indicates the distance, measured in kilometers, from a given place to Delhi when traveling by rail.
-
D.
distanceToChandigarh_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Chandigarh.
-
E.
distanceFromChandigarh_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Chandigarh.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d2e5e588190ac3a6f612d4fb54b |
completed | April 20, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:41 p.m.