Triple
T23901546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peñón de Vélez de la Gomera |
E601058
|
entity |
| Predicate | formerGeographicalForm |
P154013
|
FINISHED |
| Object | island |
—
|
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: island | Statement: [Peñón de Vélez de la Gomera, formerGeographicalForm, island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerGeographicalForm Context triple: [Peñón de Vélez de la Gomera, formerGeographicalForm, island]
-
A.
formerNameOfAreaWithin
Indicates that one area previously had a different name while remaining within the same larger encompassing area.
-
B.
formerNameOfProvince
Indicates that one name was previously used as the official name of a province before being replaced by another name.
-
C.
formerNameOfDistrict
Indicates that one district previously had a different official name, which is the value linked by this predicate.
-
D.
formerName
Indicates that an entity was previously known by a different name in the past.
-
E.
regionHistoricalName
Indicates that a region has been known by a particular historical name during some past period.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdde91d081908df44442a20e0fd2 |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f167dca3608190ace9d2eef56b2af6 |
completed | April 29, 2026, 2:07 a.m. |
Created at: April 17, 2026, 8:26 p.m.