Triple
T33604114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ENRY |
E860800
|
entity |
| Predicate | associatedAirportLongitude |
P205233
|
FINISHED |
| Object | 10.7856 E |
—
|
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: 10.7856 E | Statement: [ENRY, associatedAirportLongitude, 10.7856 E]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportLongitude Context triple: [ENRY, associatedAirportLongitude, 10.7856 E]
-
A.
associatedAirport
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
B.
associatedAirportLocalName
Indicates the local or native-language name of the airport that is associated with the given entity.
-
C.
associatedAirportFocusCityFor
Indicates that an airport serves as a designated focus city for a particular airline or carrier.
-
D.
airportLocationRelation
Indicates a spatial or administrative relationship specifying where an airport is located relative to a geographic area or jurisdiction.
-
E.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:41 a.m.