Triple
T30670982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkutun-Dagi field |
E780791
|
entity |
| Predicate | belongsToLicenseArea |
P136455
|
FINISHED |
| Object | Sakhalin-1 license area |
—
|
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: Sakhalin-1 license area | Statement: [Arkutun-Dagi field, belongsToLicenseArea, Sakhalin-1 license area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToLicenseArea Context triple: [Arkutun-Dagi field, belongsToLicenseArea, Sakhalin-1 license area]
-
A.
licenseArea
chosen
Indicates the geographic or jurisdictional scope within which a license grants permission or is legally valid.
-
B.
hasAreaName
Indicates that an entity is associated with a specific named geographic or administrative area.
-
C.
includesAreaOf
Indicates that one entity encompasses or contains the spatial extent or area covered by another entity.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
hasAreaNumber
Indicates that an entity is associated with a specific area identified by a numerical code.
- 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_69f224a7fc208190a07d6d3879b31640 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: April 29, 2026, 8:31 p.m.