Triple
T3454133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sardar Vallabhbhai Patel International Airport |
E72859
|
entity |
| Predicate | servesType |
P48322
|
FINISHED |
| Object | civil aviation |
—
|
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: civil aviation | Statement: [Sardar Vallabhbhai Patel International Airport, servesType, civil aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesType Context triple: [Sardar Vallabhbhai Patel International Airport, servesType, civil aviation]
-
A.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
B.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
C.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
D.
alsoServes
Indicates that an entity, in addition to its primary role or function, provides service or support to another specified entity or group.
-
E.
categoryOfPeopleServed
Indicates the type or group of people that are the primary recipients or beneficiaries of a service or activity.
- F. None of above. chosen
Provenance (4 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbaa457fc8190824ca00254e962f9 |
completed | March 8, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69adae041d588190a84a02bca94adec8 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:16 p.m.