Triple
T2488705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keoladeo National Park |
E55988
|
entity |
| Predicate | distanceFromAgra |
P40347
|
FINISHED |
| Object | about 55 kilometers |
—
|
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 55 kilometers | Statement: [Keoladeo National Park, distanceFromAgra, about 55 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromAgra Context triple: [Keoladeo National Park, distanceFromAgra, about 55 kilometers]
-
A.
distanceFromMathura
Indicates the spatial distance between a given entity or location and the city of Mathura.
-
B.
distanceFromVaranasi
Indicates the measured or specified distance between a given entity or location and the city of Varanasi.
-
C.
distanceFromJaipur
Indicates the spatial distance between a given entity and the location Jaipur.
-
D.
distanceToDelhiByRoad_km
Indicates the road travel distance, measured in kilometers, from a given place to Delhi.
-
E.
distanceFromJaisalmer
Indicates the measured spatial distance between a given entity and the location of Jaisalmer.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:45 p.m.