Triple
T20385280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFI's 100 Years...100 Heroes & Villains |
E497942
|
entity |
| Predicate | numberOfHeroesListed |
P139914
|
FINISHED |
| Object | 50 |
—
|
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: 50 | Statement: [AFI's 100 Years...100 Heroes & Villains, numberOfHeroesListed, 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHeroesListed Context triple: [AFI's 100 Years...100 Heroes & Villains, numberOfHeroesListed, 50]
-
A.
includesHeroes
Indicates that something (such as a work, group, or collection) contains or features one or more heroes as part of it.
-
B.
numberOfPlayableCharacters
Indicates the total count of distinct characters that can be actively controlled or played by a user in a game or interactive experience.
-
C.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
D.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
-
E.
totalChampionsCount
Indicates the total number of champions associated with or involved in a given context or 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790a31a4819099b2e6df2bafe547 |
completed | April 20, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:28 a.m.