Triple
T19956880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cronk-ny-Mona |
E479705
|
entity |
| Predicate | turnType |
P138015
|
FINISHED |
| Object | right-hand bends |
—
|
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: right-hand bends | Statement: [Cronk-ny-Mona, turnType, right-hand bends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnType Context triple: [Cronk-ny-Mona, turnType, right-hand bends]
-
A.
turns
Indicates a change in orientation, direction, or state initiated by one entity affecting itself or another entity.
-
B.
turnoverType
Indicates the specific category or nature of a turnover event, such as how or why control of an asset, position, or role changes from one party to another.
-
C.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
D.
turnedPro
Indicates that an individual transitioned from amateur status to professional status in a particular field or activity.
-
E.
isTurnBased
Indicates that an activity, process, or interaction proceeds in discrete turns where participants act one after another rather than simultaneously.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65af08e008190a3a1b807b638a99e |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f7e4848190b431a69ec3f1b609 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:54 p.m.