Triple
T10176476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuckoo Orpington |
E235864
|
entity |
| Predicate | hasGeneralAppearance |
P311
|
FINISHED |
| Object | rounded |
—
|
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: rounded | Statement: [Cuckoo Orpington, hasGeneralAppearance, rounded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeneralAppearance Context triple: [Cuckoo Orpington, hasGeneralAppearance, rounded]
-
A.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
B.
appearance
chosen
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
C.
hasMediaAppearanceIn
Indicates that an entity appears or is featured as media content within a specified media work, program, or publication.
-
D.
allegedAppearanceType
Indicates the type or nature of an appearance that is claimed or reported to have occurred, without confirming that the appearance actually took place.
-
E.
typicalAppearanceContext
Indicates the usual situation, setting, or context in which an entity most commonly appears or is typically encountered.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdecd3a2688190bce277bffffcbf8b |
completed | April 2, 2026, 4:13 a.m. |
| PD | Predicate disambiguation | batch_69cd7c79f21c8190a7f31b2eab80b8ba |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:11 p.m.