Triple
T26564321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Przewalski’s horse |
E666333
|
entity |
| Predicate | domesticHorseChromosomeNumber |
P13235
|
FINISHED |
| Object | 64 |
—
|
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: 64 | Statement: [Przewalski’s horse, domesticHorseChromosomeNumber, 64]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: domesticHorseChromosomeNumber Context triple: [Przewalski’s horse, domesticHorseChromosomeNumber, 64]
-
A.
chromosomeNumber
chosen
Indicates the specific count of chromosomes associated with an organism, cell, or genetic entity.
-
B.
chromosomeBaseNumber
Indicates the fundamental or characteristic number of distinct chromosomes that typically occur in a complete (haploid) set for a given organism or taxon.
-
C.
horseBreed
Indicates that one entity is a specific breed of the horse represented by the other entity.
-
D.
horseColor
Indicates the relationship that specifies what color a given horse is.
-
E.
featuresHorse
Indicates that something includes, presents, or prominently involves a horse as a central element or subject.
- 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_69ee9cf7e94481909f0d556b36e43572 |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6149cc0c88190aadaacfa45a2382e |
completed | May 2, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 1:54 a.m.