Triple
T27144003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgiana Hurdle |
E681890
|
entity |
| Predicate | typicalAgeOfHorses |
P200405
|
FINISHED |
| Object | Mature hurdlers |
—
|
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: Mature hurdlers | Statement: [Morgiana Hurdle, typicalAgeOfHorses, Mature hurdlers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAgeOfHorses Context triple: [Morgiana Hurdle, typicalAgeOfHorses, Mature hurdlers]
-
A.
typicalAttributesOfHorse
Indicates the standard or commonly expected characteristics or properties associated with a horse.
-
B.
featuresHorse
Indicates that something includes, presents, or prominently involves a horse as a central element or subject.
-
C.
approximateNumberOfHorses
Indicates an estimated or roughly calculated count of horses associated with a given subject.
-
D.
horseBreed
Indicates that one entity is a specific breed of the horse represented by the other entity.
-
E.
mostSuccessfulHorseYears
Indicates the years during which a particular horse achieved its highest level of success or best performance relative to other years.
- F. None of above. chosen
Provenance (4 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69ff891e4b9c8190aa86a339a8944496 |
completed | May 9, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69ff8801180c8190b23e20996ca68e0a |
completed | May 9, 2026, 7:16 p.m. |
| PDg | Predicate description generation | batch_69ff891d54248190be8742197564605a |
completed | May 9, 2026, 7:21 p.m. |
Created at: April 27, 2026, 9:10 a.m.