Triple
T27882776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMSM |
E705137
|
entity |
| Predicate | associatedAirportPrimaryCityServed |
P16381
|
FINISHED |
| Object | Mexico City |
—
|
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: Mexico City | Statement: [MMSM, associatedAirportPrimaryCityServed, Mexico City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirportPrimaryCityServed Context triple: [MMSM, associatedAirportPrimaryCityServed, Mexico City]
-
A.
associatedAirportServes
Indicates that a given airport provides service to, or is used by, the associated entity (such as a city, region, or facility).
-
B.
airportServed
Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
-
C.
associatedAirportFocusCityFor
Indicates that an airport serves as a designated focus city for a particular airline or carrier.
-
D.
airportServesAs
chosen
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
-
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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_6a008098e5dc8190b7ccad8bab780343 |
completed | May 10, 2026, 12:56 p.m. |
| PD | Predicate disambiguation | batch_6a008037267c8190990225a6ff0b3694 |
completed | May 10, 2026, 12:55 p.m. |
Created at: April 27, 2026, 6:31 p.m.