Triple
T34525181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GMR Goa International Airport Limited |
E886380
|
entity |
| Predicate | projectLocationCountry |
P95032
|
FINISHED |
| Object | India |
—
|
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: India | Statement: [GMR Goa International Airport Limited, projectLocationCountry, India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: projectLocationCountry Context triple: [GMR Goa International Airport Limited, projectLocationCountry, India]
-
A.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
B.
siteCountry
Indicates that a site is located within or associated with a specific country.
-
C.
currentLocationCountry
Indicates that one entity is the country in which another entity is currently located.
-
D.
projectCountryAtTheTime
chosen
Indicates the country with which a project was associated at the specific time or period in question.
-
E.
locationCountryAtTheTime
Indicates that an entity was located in a specified country during a particular time or time period.
- 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_69f349cd7c148190aa99192b126d1527 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb788ec8190a1afec0cfb77dfa5 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:02 a.m.