Triple
T16247530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loco Dempsey |
E394411
|
entity |
| Predicate | numberOfHeroinesGroup |
P85078
|
FINISHED |
| Object | three |
—
|
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: three | Statement: [Loco Dempsey, numberOfHeroinesGroup, three]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHeroinesGroup Context triple: [Loco Dempsey, numberOfHeroinesGroup, three]
-
A.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
-
B.
numberOfMainFemaleLeadsInWork
chosen
Indicates the number of primary female lead characters that appear in a given work.
-
C.
hasProtagonistGroup
Indicates that a narrative work features a central group of characters who collectively serve as the main protagonists.
-
D.
numberOfGroups
Indicates the total count of distinct groups associated with or formed within a given context or entity.
-
E.
numberOfHonoredWomen
Indicates the count of women who have been honored or recognized in a given context or event.
- F. None of above.
Provenance (3 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245942460819080897afad0d2fe09 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.