Triple
T6721966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Animal Wall |
E153417
|
entity |
| Predicate | originalNumberOfSculptures |
P22479
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Animal Wall, originalNumberOfSculptures, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNumberOfSculptures Context triple: [Animal Wall, originalNumberOfSculptures, 9]
-
A.
numberOfSculptures
chosen
Indicates the quantity of sculptures associated with a given entity or context.
-
B.
numberOfPaintedSculptures
Indicates the quantity of sculptures that have been painted in a given context or collection.
-
C.
completionOfSculptures
Indicates that one entity is responsible for finishing or bringing to completion the creation or production of sculptures associated with another entity.
-
D.
estimatedNumberOfPaintings
Indicates the approximate count of paintings associated with an entity, rather than an exact, verified number.
-
E.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d139d50c81908b19120f139deaa5 |
completed | March 27, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69c6d08c5d348190a29dee668c398e70 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:08 p.m.