Triple
T14182519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Men We Reaped |
E351490
|
entity |
| Predicate | numberOfPeoplePortrayed |
P6685
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Men We Reaped, numberOfPeoplePortrayed, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPeoplePortrayed Context triple: [Men We Reaped, numberOfPeoplePortrayed, 5]
-
A.
numberOfPersons
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
B.
numberOfFiguresDepicted
chosen
Indicates the total count of distinct figures shown within a given depiction or representation.
-
C.
peopleCountDescriptor
Indicates how the number of people involved in a situation, group, or context is characterized or described.
-
D.
numberOfHumanProtagonists
Indicates the count of human characters that serve as protagonists in a given work or context.
-
E.
containsHumanFigures
Indicates that the subject includes one or more human figures within its content or composition.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61ca3ad88190944850c97760dcbf |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:02 a.m.