Triple
T29148571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wish Upon |
E738838
|
entity |
| Predicate | numberOfWishesInPlot |
P201181
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Wish Upon, numberOfWishesInPlot, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfWishesInPlot Context triple: [Wish Upon, numberOfWishesInPlot, 7]
-
A.
numberOfVisions
Indicates the quantity of visions experienced or associated with an entity.
-
B.
usedInPlot
Indicates that something (e.g., an object, idea, or element) is employed as a component or device within the storyline or narrative structure of a plot.
-
C.
protagonistCount
Indicates the number of primary protagonists involved in a given narrative or work.
-
D.
influencesPlotOf
Indicates that one entity has an effect on or helps shape the storyline or narrative development of another entity.
-
E.
settingInPlot
Indicates that a particular setting or location serves as the backdrop or environment in which the events of a plot take place.
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69ffdd0486e08190a0f2ff4ce0aee13b |
completed | May 10, 2026, 1:19 a.m. |
Created at: April 28, 2026, 11:41 a.m.