Triple
T17289852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spotted Horses panel |
E419754
|
entity |
| Predicate | numberOfMainFigures |
P86634
|
FINISHED |
| Object | two large horses |
—
|
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: two large horses | Statement: [Spotted Horses panel, numberOfMainFigures, two large horses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainFigures Context triple: [Spotted Horses panel, numberOfMainFigures, two large horses]
-
A.
numberOfFiguresDepicted
Indicates the total count of distinct figures shown within a given depiction or representation.
-
B.
numberOfMainElements
chosen
Indicates the quantity of primary or central elements associated with an entity or structure.
-
C.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
-
D.
numberOfMainImpostors
Indicates the count of primary or main impostor entities involved in a given context or scenario.
-
E.
containsHumanFigures
Indicates that the subject includes one or more human figures within its content or composition.
- 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e43782b7ac8190b702567e9ccf9a35 |
completed | April 19, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69e3b0118ad08190b119cd219c68ba67 |
completed | April 18, 2026, 4:23 p.m. |
Created at: April 10, 2026, 5:40 a.m.