Triple
T28186886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZIPPY |
E716203
|
entity |
| Predicate | associatedWithAirlineHeadquartersLocation |
P12361
|
FINISHED |
| Object | Narita, Chiba Prefecture, Japan |
—
|
NE NERFINISHED |
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: Narita, Chiba Prefecture, Japan | Statement: [ZIPPY, associatedWithAirlineHeadquartersLocation, Narita, Chiba Prefecture, Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAirlineHeadquartersLocation Context triple: [ZIPPY, associatedWithAirlineHeadquartersLocation, Narita, Chiba Prefecture, Japan]
-
A.
linkedAirlineHeadquartersLocation
Indicates that an airline’s headquarters is located in the specified place or facility.
-
B.
associatedAirlineHeadquarters
chosen
Indicates that an airline is connected to or based at a particular headquarters location.
-
C.
associatedAirlineHeadquartersIsland
Indicates that an airline’s headquarters are located on a specific island.
-
D.
associatedWithAirportName
Indicates a relationship where an entity is linked or connected to a specific airport by its name.
-
E.
associatedAirportPrimaryHubFor
Indicates that an airport serves as the primary hub for a particular airline or transportation operator.
- 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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a00cbae75988190974f5b45a2e62326 |
completed | May 10, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_6a00cabe4c5881909cca5efbe494e0d1 |
completed | May 10, 2026, 6:13 p.m. |
Created at: April 27, 2026, 10:23 p.m.