Triple
T28500858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De'ang |
E721224
|
entity |
| Predicate | regionTypeOfHabitation |
P75000
|
FINISHED |
| Object | mountain slopes and highlands |
—
|
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: mountain slopes and highlands | Statement: [De'ang, regionTypeOfHabitation, mountain slopes and highlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionTypeOfHabitation Context triple: [De'ang, regionTypeOfHabitation, mountain slopes and highlands]
-
A.
regionTypeOfPlace
Indicates that a place belongs to or is categorized under a specific type of geographic or administrative region.
-
B.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
C.
regionOfHabitation
chosen
Indicates the geographic area or environment in which an entity typically lives or resides.
-
D.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
E.
humanSettlementType
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd19f791f48190bbb6f6047f9ddc59 |
completed | May 7, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fd0df365948190bc9bfc7ffd46acd8 |
completed | May 7, 2026, 10:10 p.m. |
Created at: April 28, 2026, 3:06 a.m.