Triple
T2986675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angora |
E80641
|
entity |
| Predicate | associatedWithTextile |
P2830
|
FINISHED |
| Object | mohair |
—
|
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: mohair | Statement: [Angora, associatedWithTextile, mohair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTextile Context triple: [Angora, associatedWithTextile, mohair]
-
A.
associatedWithText
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
B.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
C.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
D.
associatedWithFormat
Indicates a relationship where something is linked or connected to a particular format or formatting standard.
-
E.
associatedWithUnit
Indicates that one entity has a connection, linkage, or affiliation with a particular unit (such as a division, department, or organizational subunit).
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c88f608190bf734e0b744bf3d1 |
completed | March 8, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69ad9611fc348190a5d17d237f653f60 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.