Triple
T7967004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molinero |
E185229
|
entity |
| Predicate | relatedWordInSpanish |
P10003
|
FINISHED |
| Object | molino |
—
|
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: molino | Statement: [Molinero, relatedWordInSpanish, molino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedWordInSpanish Context triple: [Molinero, relatedWordInSpanish, molino]
-
A.
linguisticallyRelatedTo
chosen
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
B.
cognateInArabic
Indicates that a given term has a corresponding cognate form in Arabic that is historically or linguistically related in origin or structure.
-
C.
cognateOf
Indicates that two linguistic forms share a common historical origin, typically descending from the same ancestral word.
-
D.
equivalentInZapotec
Indicates that two linguistic elements are equivalent in meaning or function within the Zapotec language.
-
E.
equivalentEpithetInNahuatl
Indicates that one entity’s epithet has an equivalent or corresponding epithet expressed in the Nahuatl 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ba3f53c8190a0e9b3de2f1b9645 |
completed | March 31, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69cb0473d7dc8190a25d0cf460b9fcbe |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:13 p.m.