Triple
T5088669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black on Maroon |
E114698
|
entity |
| Predicate | intendedViewingDistance |
P60647
|
FINISHED |
| Object | close, enveloping proximity |
—
|
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: close, enveloping proximity | Statement: [Black on Maroon, intendedViewingDistance, close, enveloping proximity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedViewingDistance Context triple: [Black on Maroon, intendedViewingDistance, close, enveloping proximity]
-
A.
viewingDistanceFromFalls
Indicates the distance from which an observer views or experiences the falls.
-
B.
minimumWorkingDistance
Indicates the shortest allowable distance that must be maintained between two entities for them to operate or interact safely or effectively.
-
C.
canBeSeenWith
Indicates that two entities are observable together in the same context, setting, or time.
-
D.
eyeRelief
Indicates the distance between an eyepiece and the observer’s eye at which the full field of view can be comfortably seen.
-
E.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
- 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_69bd443e941881908eb4e8c685b6f656 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd753f6544819090c028b34ee87536 |
completed | March 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69bd715c0a448190afc837c6c31dc6ab |
completed | March 20, 2026, 4:10 p.m. |
| PDg | Predicate description generation | batch_69bd72b8d7a88190ad53fae64f17e22c |
completed | March 20, 2026, 4:15 p.m. |
Created at: March 20, 2026, 1:40 p.m.