Triple
T10181856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khowai |
E236803
|
entity |
| Predicate | distanceToMBBAirport_km |
P92564
|
FINISHED |
| Object | approximately 55 |
—
|
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: approximately 55 | Statement: [Khowai, distanceToMBBAirport_km, approximately 55]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMBBAirport_km Context triple: [Khowai, distanceToMBBAirport_km, approximately 55]
-
A.
distanceToAirport
Indicates the measured distance between a given location and the nearest or specified airport.
-
B.
distanceToFrankfurtAirport_km
Indicates the physical distance, measured in kilometers, between a given location and Frankfurt Airport.
-
C.
distanceToOsloAirportGardermoen_km
Indicates the physical distance, measured in kilometers, between a given location and Oslo Airport Gardermoen.
-
D.
distanceFromLombokInternationalAirport
Indicates the measured distance between a given location and Lombok International Airport.
-
E.
distanceFromMiyakoAirport
Indicates the measured distance between a given location and Miyako Airport.
- 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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded32b91c8190b01ad37b2456080a |
completed | April 2, 2026, 4:14 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:12 p.m.