Triple
T22626089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Diagonal of May 25, 1963 (to Constantin Brancusi) |
E558420
|
entity |
| Predicate | numberOfLightTubes |
P10372
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [The Diagonal of May 25, 1963 (to Constantin Brancusi), numberOfLightTubes, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfLightTubes Context triple: [The Diagonal of May 25, 1963 (to Constantin Brancusi), numberOfLightTubes, 1]
-
A.
numberOfTubes
chosen
Indicates the quantity of tubes associated with or contained by a given entity.
-
B.
numberOfLights
Indicates the quantity of lights associated with or present on a given entity.
-
C.
typeOfLampsUsed
Indicates the specific kinds or categories of lamps that are utilized in a given context or system.
-
D.
hasNumberOfMainLights
Indicates the relationship that specifies how many primary or main lights are associated with an entity.
-
E.
hasNumberOfCables
Indicates the relationship that specifies how many cables are associated with a given 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e3d55b081908930ebff4372154f |
completed | April 29, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 3:01 p.m.