Triple
T36701672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bolso |
E906243
|
entity |
| Predicate | genderInSpanish |
P138967
|
FINISHED |
| Object | masculine noun |
—
|
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: masculine noun | Statement: [Bolso, genderInSpanish, masculine noun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderInSpanish Context triple: [Bolso, genderInSpanish, masculine noun]
-
A.
grammaticalGenderInSpanish
chosen
Indicates that the entity has the specified grammatical gender (masculine, feminine, or neuter) in the Spanish language.
-
B.
hasGenderInPortuguese
Indicates that a term or entity is associated with a specific grammatical gender in the Portuguese language.
-
C.
genderOfName
Indicates the gender typically associated with a given name.
-
D.
genderAsHuman
Indicates that the specified entity has a particular human gender (e.g., male, female) assigned or identified.
-
E.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7ed5bcc8190957e36ffd0a16733 |
completed | May 3, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.