Triple
T16632967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zangilan District |
E404120
|
entity |
| Predicate | borderTypeWithArmenia |
P123655
|
FINISHED |
| Object | land border |
—
|
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: land border | Statement: [Zangilan District, borderTypeWithArmenia, land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTypeWithArmenia Context triple: [Zangilan District, borderTypeWithArmenia, land border]
-
A.
borderTypeWithTurkmenistan
Indicates the type or nature of the border relationship that an entity has with Turkmenistan.
-
B.
borderTypeWithMongolia
Indicates the specific nature or classification of the border that an entity shares with Mongolia.
-
C.
borderTypeWithEthiopia
Indicates the specific nature or classification of the border relationship that an entity has with Ethiopia.
-
D.
borderTypeWithGulfOfAden
Indicates that an entity’s border is specifically characterized as adjoining or interacting with the Gulf of Aden.
-
E.
borderTypeWithYemen
Indicates the type or nature of the border that exists between a given entity and Yemen.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e7d4a48190a9b4a14ecbb2a14b |
completed | April 18, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_69e296ad3f148190af09223dc35b155c |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.