Triple
T17104606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcelona Chair |
E415064
|
entity |
| Predicate | legForm |
P23297
|
FINISHED |
| Object | curved X-shaped legs |
—
|
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: curved X-shaped legs | Statement: [Barcelona Chair, legForm, curved X-shaped legs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legForm Context triple: [Barcelona Chair, legForm, curved X-shaped legs]
-
A.
legs
Indicates that an entity possesses legs, specifying the presence or number of leg-like appendages associated with it.
-
B.
legOrientation
Indicates the relative positioning or directional alignment of an entity’s leg(s) with respect to a reference frame or another object.
-
C.
legOrder
Indicates the sequential position or ordering of a specific leg within a multi-leg structure, process, or route.
-
D.
legFeathering
Indicates that an entity possesses feathers growing on or covering its legs.
-
E.
legCharacteristic
chosen
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2591a881909c5f4f7db47f4d6c |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.