Triple
T10212485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tortoise and the Hare |
E242362
|
entity |
| Predicate | featuresRaceBetween |
P92743
|
FINISHED |
| Object | tortoise |
—
|
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: tortoise | Statement: [The Tortoise and the Hare, featuresRaceBetween, tortoise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRaceBetween Context triple: [The Tortoise and the Hare, featuresRaceBetween, tortoise]
-
A.
racesAgainst
Indicates that one entity competes in a race directly against another entity.
-
B.
raceMeeting
Indicates a competitive event where multiple participants race against each other under shared rules and conditions.
-
C.
racingNumber
Indicates that an entity has been assigned a specific competition or race identification number used to distinguish it from other participants.
-
D.
raceWon
Indicates that one participant has achieved victory in a race or competitive event over others.
-
E.
racedIn
Indicates that an entity participated as a competitor in a particular race or racing event.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa23bce881909b5deac612ec22cb |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
| PDg | Predicate description generation | batch_69d3aa208c248190a0fb186b106389f3 |
completed | April 6, 2026, 12:42 p.m. |
Created at: April 6, 2026, 11:02 a.m.