Triple
T13729240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | vaquita marina |
E329747
|
entity |
| Predicate | rasgoDistintivo |
P662
|
FINISHED |
| Object | manchas oscuras alrededor de los ojos |
—
|
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: manchas oscuras alrededor de los ojos | Statement: [vaquita marina, rasgoDistintivo, manchas oscuras alrededor de los ojos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rasgoDistintivo Context triple: [vaquita marina, rasgoDistintivo, manchas oscuras alrededor de los ojos]
-
A.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
B.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
C.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
D.
catalogCharacteristic
Indicates that a catalog has a specific characteristic or attribute associated with it.
-
E.
primaryCharacteristics
Indicates the main defining traits or features that most fundamentally characterize an entity.
- 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.