Triple
T46227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cottonopolis |
E905
|
entity |
| Predicate | etymologyComponent |
P506
|
FINISHED |
| Object | cotton |
—
|
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: cotton | Statement: [Cottonopolis, etymologyComponent, cotton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologyComponent Context triple: [Cottonopolis, etymologyComponent, cotton]
-
A.
etymology
Indicates the historical origin and development of a word or term, including its source language and form.
-
B.
etymologicalLanguage
chosen
Indicates the language from which a word or term is historically derived in its etymology.
-
C.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
D.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
E.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24b1bf2c081908f20e13939b713ff |
completed | Feb. 28, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69a24abd07508190a83ffba5368c1c79 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.