Triple
T35563259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The West Point Story |
E1027693
|
entity |
| Predicate | featuresDanceDirectionBy |
P207049
|
FINISHED |
| Object | LeRoy Prinz |
E1944968
|
NE 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: LeRoy Prinz | Statement: [The West Point Story, featuresDanceDirectionBy, LeRoy Prinz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDanceDirectionBy Context triple: [The West Point Story, featuresDanceDirectionBy, LeRoy Prinz]
-
A.
danceDirection
Indicates the direction or orientation in which the dancing action is performed or moves.
-
B.
danceProp
Indicates that one entity is used or involved as a prop in another entity’s dance performance or dancing activity.
-
C.
learnsToDanceIn
Indicates that an entity is in the process of acquiring or practicing dancing skills within a particular place or context.
-
D.
typeOfDanceFeatured
Indicates the specific style or category of dance that is highlighted or showcased in a given context or work.
-
E.
danceFeature
Indicates that one entity serves as a notable characteristic, element, or attribute of a dance or dancing-related activity.
- F. None of above. chosen
Provenance (5 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3852fb52e48190a56e85f36ada017f |
completed | June 21, 2026, 9:09 p.m. |
| PD | Predicate disambiguation | batch_6a037a04d8348190a4819666eab42c9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:04 p.m.