Triple
T7018209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOAT |
E162748
|
entity |
| Predicate | associatedAirportGeographicRegion |
P75280
|
FINISHED |
| Object | southern India |
—
|
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: southern India | Statement: [VOAT, associatedAirportGeographicRegion, southern India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportGeographicRegion Context triple: [VOAT, associatedAirportGeographicRegion, southern India]
-
A.
associatedAirportICAOSubregion
Indicates a relationship where an airport is linked to the specific ICAO-defined subregion in which it is located or with which it is operationally associated.
-
B.
hasAirportCodeRegion
Indicates that an airport code is associated with, or belongs to, a specific geographic or administrative region.
-
C.
hasRegionalAirport
Indicates that a place or region possesses or is served by a regional airport.
-
D.
airlineServiceArea
Indicates the geographic regions or locations where an airline operates or provides service.
-
E.
geographicalRegionType
Indicates the specific kind or category of geographical region that an entity belongs to (e.g., continent, country, province, or city).
- 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_69c6885a127c8190867b059bdccf13ff |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e5ecd4488190bf19e42de55da98b |
completed | March 27, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b8118481909d76eb6616160e80 |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e5eb904481909a900e2ba9df710b |
completed | March 27, 2026, 8:17 p.m. |
Created at: March 27, 2026, 2:34 p.m.