Triple
T25627131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gobardanga |
E642462
|
entity |
| Predicate | distanceToKolkataApprox |
P22706
|
FINISHED |
| Object | about 50 km |
—
|
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 50 km | Statement: [Gobardanga, distanceToKolkataApprox, about 50 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKolkataApprox Context triple: [Gobardanga, distanceToKolkataApprox, about 50 km]
-
A.
distanceFromKolkata
chosen
Indicates the spatial distance between a given location and the city of Kolkata.
-
B.
distanceToSiliguri_km
Indicates the physical distance, measured in kilometers, between a given location and Siliguri.
-
C.
distanceFromMumbaiApproxKm
Indicates the approximate physical distance, measured in kilometers, between a given location and Mumbai.
-
D.
distanceToDelhiApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Delhi.
-
E.
distanceToJamshedpur_km
Indicates the physical distance, measured in kilometers, between a given location and Jamshedpur.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: April 21, 2026, 5:15 p.m.