Triple
T835875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garter riband |
E18067
|
entity |
| Predicate | positionOnBody |
P5132
|
FINISHED |
| Object | worn over the left shoulder |
—
|
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: worn over the left shoulder | Statement: [Garter riband, positionOnBody, worn over the left shoulder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnBody Context triple: [Garter riband, positionOnBody, worn over the left shoulder]
-
A.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
B.
positionB
chosen
Indicates that one entity occupies or is located at a specific position relative to another entity.
-
C.
hasPositionOn
Indicates that one entity occupies or holds a specific role, job, or spatial location relative to another entity.
-
D.
seatOnBody
Indicates that one entity functions as a seat or seating surface that is physically attached or integrated to a body or body-like structure.
-
E.
positionOnGood
Indicates the stance or viewpoint an entity holds regarding a particular good, such as support, opposition, or neutrality.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abce08348190b716e3ce5a638f99 |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7c7df881909c539c3ab8ff0367 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.