Triple
T12871500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ALG |
E307859
|
entity |
| Predicate | associatedCityIATACode |
P6089
|
FINISHED |
| Object | ALG |
—
|
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: ALG | Statement: [ALG, associatedCityIATACode, ALG]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCityIATACode Context triple: [ALG, associatedCityIATACode, ALG]
-
A.
associatedAirport
Indicates a relationship where an entity is linked or connected to a specific airport, typically as its relevant or corresponding airport.
-
B.
associatedCityCode
Indicates that an entity is linked or related to a specific city identified by its code.
-
C.
hasAirportCodeCity
chosen
Indicates that a city is associated with a specific airport code (such as an IATA or ICAO code) that identifies its airport.
-
D.
airportCodeContext
Indicates that an airport code is being used or interpreted within a specific contextual framework (such as a region, system, or standard) that defines its meaning.
-
E.
otherAirportOfCity
Indicates that the subject airport is another airport serving the same city as the object 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:38 p.m.