Triple
T22983538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamnagar Airport |
E571535
|
entity |
| Predicate | isMilitaryCivil |
P71540
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Jamnagar Airport, isMilitaryCivil, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMilitaryCivil Context triple: [Jamnagar Airport, isMilitaryCivil, true]
-
A.
isCivilMilitary
chosen
Indicates that an entity or relationship involves both civilian and military components or functions.
-
B.
civilOrMilitary
Indicates that something is classified as either civil (non-military) or military in nature or function.
-
C.
isCivilian
Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
-
D.
derivedFromMilitaryOrCivil
Indicates that something originates from, is based on, or is obtained through military or civil (non-military governmental) sources, activities, or contexts.
-
E.
civilian
Indicates that an entity is a non-military person or object associated with civilian status or context.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1829775e881909c5d6d35d3fd57f7 |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b974e7c8190b8be11dbb4518693 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:49 p.m.