Triple
T9177183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buff Orpington |
E220230
|
entity |
| Predicate | hasBodySize |
P3593
|
FINISHED |
| Object | large |
—
|
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: large | Statement: [Buff Orpington, hasBodySize, large]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodySize Context triple: [Buff Orpington, hasBodySize, large]
-
A.
hasBodyOf
Indicates that one entity possesses, contains, or is composed of the physical body or main substance of another entity.
-
B.
hasBodyLengthRange
Indicates the range of possible body lengths associated with an entity, typically expressed as a minimum and maximum value.
-
C.
memberOfBodySize
Indicates that one entity is a component or part whose size contributes to or characterizes the overall body size of another entity.
-
D.
hasInternalBody
Indicates that one entity possesses an internal body or internal bodily structure relative to another entity or context.
-
E.
bodySize
chosen
Indicates the relative physical magnitude or scale of an entity’s body, such as how large or small it is.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccbfa60c3c8190b6335b9067de5b72 |
completed | April 1, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:23 p.m.