Triple
T33408223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chagu Chagu Umakko |
E855496
|
entity |
| Predicate | approximateNumberOfHorses |
P198397
|
FINISHED |
| Object | around 100 |
—
|
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: around 100 | Statement: [Chagu Chagu Umakko, approximateNumberOfHorses, around 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfHorses Context triple: [Chagu Chagu Umakko, approximateNumberOfHorses, around 100]
-
A.
approximateNumberOfZebra
Indicates that one entity specifies an estimated or approximate count of zebras associated with another entity.
-
B.
numberOfStoneHorses
Indicates the quantity of stone horses associated with a given subject or location.
-
C.
eligibleHorses
Indicates that certain horses meet the required conditions or criteria to qualify for a specified status, event, or action.
-
D.
horseName
Indicates that an entity has the specified name of a horse.
-
E.
horseBreed
Indicates that one entity is a specific breed of the horse represented by the other entity.
- 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_69f3496f04a08190804e56ac5098b8e4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fee0b2da3c8190a3519d0564f2f32d |
completed | May 9, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69fee05b315c819081dfcbfb15273487 |
completed | May 9, 2026, 7:20 a.m. |
| PDg | Predicate description generation | batch_69fee0b03a0c81909117dc5915d77295 |
completed | May 9, 2026, 7:22 a.m. |
Created at: May 1, 2026, 1:36 a.m.