Triple
T25397814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimapur Airport |
E636338
|
entity |
| Predicate | operationalType |
P819
|
FINISHED |
| Object | domestic flights |
—
|
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: domestic flights | Statement: [Dimapur Airport, operationalType, domestic flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operationalType Context triple: [Dimapur Airport, operationalType, domestic flights]
-
A.
operationType
Indicates the specific kind of operation or action being performed or recorded in the relationship between entities.
-
B.
operationalNature
Indicates the functional or practical manner in which an entity, process, or system operates or carries out its activities.
-
C.
typeOfOperation
chosen
Indicates the specific kind or category of operation being performed or referenced in a given context.
-
D.
typicalOperatorType
Indicates the usual or most common type or category of operator associated with a given entity or context.
-
E.
systemTypeOperated
Indicates that an entity operates, controls, or runs a particular type of system.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 21, 2026, 1:50 p.m.