Triple
T14613460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COA |
E343016
|
entity |
| Predicate | operatorSecondaryHubAirportCode |
P75290
|
FINISHED |
| Object | GUM |
E147282
|
NE 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: GUM | Statement: [COA, operatorSecondaryHubAirportCode, GUM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GUM Context triple: [COA, operatorSecondaryHubAirportCode, GUM]
-
A.
GUM
GUM is a historic and iconic department store located on Red Square in Moscow, Russia, known for its grand architecture and luxury retail offerings.
-
B.
GUM
chosen
GUM is the IATA airport code for Antonio B. Won Pat International Airport, the main commercial airport serving Guam in the western Pacific.
-
C.
Gumdag
Gumdag is a town in western Turkmenistan located within the Balkan Region, known primarily as a local center in an oil- and gas-producing area.
-
D.
Gumm
Gumm is the birth surname of American actress and singer Judy Garland, originally Frances Ethel Gumm.
-
E.
GumNebula
GumNebula is a vast, faint emission nebula in the southern sky, believed to be the remnant of one or more ancient supernova explosions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb45264988190a1df13e8b54a85bd |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda92110e88190af47b713dd24520b |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:25 a.m.