Triple
T25284226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makwanpur District |
E633893
|
entity |
| Predicate | hasStrategicTown |
P106675
|
FINISHED |
| Object | Hetauda |
—
|
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: Hetauda | Statement: [Makwanpur District, hasStrategicTown, Hetauda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrategicTown Context triple: [Makwanpur District, hasStrategicTown, Hetauda]
-
A.
wasStrategicCenterIn
Indicates that an entity functioned as a key strategic center or hub within a specified context, such as a region, period, or conflict.
-
B.
hasCoreTown
chosen
Indicates that an entity possesses or is associated with a primary or central town that serves as its main urban center.
-
C.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
D.
hasCentralTownFeature
Indicates that a town possesses a specific central feature or focal element (such as a landmark, square, or facility) that characterizes its core area.
-
E.
hasNearbyMilitaryTown
Indicates that one location is situated close to a town whose primary function or identity is associated with military presence or activity.
- 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_69e75a9402fc81909362ca85277c06d9 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 21, 2026, 1:19 p.m.