Triple
T32856408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jurançon Sec |
E840386
|
entity |
| Predicate | labelTermMeaning |
P128854
|
FINISHED |
| Object | dry |
—
|
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: dry | Statement: [Jurançon Sec, labelTermMeaning, dry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelTermMeaning Context triple: [Jurançon Sec, labelTermMeaning, dry]
-
A.
inspiredTermMeaning
Indicates that one term’s meaning is derived from, modeled after, or conceptually influenced by another term.
-
B.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
C.
meaningGloss
chosen
Indicates that the predicate provides a brief explanatory phrase or paraphrase capturing the meaning or sense of another expression or item.
-
D.
lettersMeaning
Indicates that a set of letters or characters represents, signifies, or conveys a particular meaning or message.
-
E.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
- 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_69f349412c78819084459850e11d29f7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:17 a.m.