Triple
T10780437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vasco da Gama, Goa |
E254304
|
entity |
| Predicate | distanceToDabolimAirport |
P79745
|
FINISHED |
| Object | about 4 kilometres |
—
|
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 4 kilometres | Statement: [Vasco da Gama, Goa, distanceToDabolimAirport, about 4 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDabolimAirport Context triple: [Vasco da Gama, Goa, distanceToDabolimAirport, about 4 kilometres]
-
A.
distanceToMBBAirport_km
Indicates the distance, measured in kilometers, from a given location to the MBB airport.
-
B.
distanceToAirport
chosen
Indicates the measured distance between a given location and the nearest or specified airport.
-
C.
distanceFromLombokInternationalAirport
Indicates the measured distance between a given location and Lombok International Airport.
-
D.
distanceFromGuwahati_km
Indicates the physical distance, measured in kilometers, between an entity and the location of Guwahati.
-
E.
distanceFromMiyakoAirport
Indicates the measured distance between a given location and Miyako Airport.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c384bc81908f503f3a2e0503a4 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.