Triple
T3661813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esselen language |
E77665
|
entity |
| Predicate | hasLinguisticDataType |
P50225
|
FINISHED |
| Object | word lists |
—
|
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: word lists | Statement: [Esselen language, hasLinguisticDataType, word lists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinguisticDataType Context triple: [Esselen language, hasLinguisticDataType, word lists]
-
A.
hasLinguisticFeature
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
B.
hasLinguisticDomain
Indicates that something (such as a term, expression, or resource) is associated with or applies within a particular linguistic domain or language context.
-
C.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
D.
hasLinguisticElement
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
-
E.
hasLinguisticCode
Indicates that an entity is associated with a specific linguistic identifier or code (such as a language or script code) that characterizes its linguistic properties.
- F. None of above. chosen
Provenance (4 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d826d88190b0b50e8592088a36 |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb97cdb788190a5ce96b21bd157ab |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 8, 2026, 3:25 p.m.