Triple
T35961204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aghdam region |
E1039998
|
entity |
| Predicate | statusOfMainTown |
P200551
|
FINISHED |
| Object | largely destroyed |
—
|
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: largely destroyed | Statement: [Aghdam region, statusOfMainTown, largely destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statusOfMainTown Context triple: [Aghdam region, statusOfMainTown, largely destroyed]
-
A.
mainTownOn
Indicates that one town is the primary or principal town located on or associated with a particular geographic feature, route, or area.
-
B.
hasTownStatus
Indicates that an entity possesses the legal or administrative status of being recognized as a town.
-
C.
townStatus
Indicates the administrative or legal status of a settlement as a town (e.g., whether and how it is officially recognized or classified as a town).
-
D.
mainMunicipality
Indicates that one municipality serves as the primary or central administrative municipality associated with another entity or area.
-
E.
humanSettlementStatus
Indicates the classification of a place in terms of its status as a human settlement (e.g., whether and how it is recognized or designated as a populated place).
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
| PDg | Predicate description generation | batch_69ff956cd640819081efc31f313690b0 |
completed | May 9, 2026, 8:13 p.m. |
Created at: May 3, 2026, 4:07 p.m.