Triple
T13729258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | vaquita marina |
E329747
|
entity |
| Predicate | nombreComúnEnEspañol |
P12773
|
FINISHED |
| Object | vaquita marina |
—
|
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: vaquita marina | Statement: [vaquita marina, nombreComúnEnEspañol, vaquita marina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nombreComúnEnEspañol Context triple: [vaquita marina, nombreComúnEnEspañol, vaquita marina]
-
A.
hasNameInSpanish
chosen
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
B.
languageCommonlyCalled
Indicates that one language is commonly referred to or known by a particular alternative name or label.
-
C.
officialNameInSpanish
Indicates the officially recognized name of an entity when expressed in the Spanish language.
-
D.
hasLongNameInSpanish
Indicates that an entity is known by a long or extended name when expressed in the Spanish language.
-
E.
hasNameInCatalan
Indicates that an entity is associated with a specific name expressed in the Catalan language.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f746cc8190abde237bbb7e6c78 |
completed | April 14, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:55 p.m.