Triple
T7272182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The 100: A Ranking of the Most Influential Persons in History |
E161132
|
entity |
| Predicate | listsNumberOfPeople |
P2307
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [The 100: A Ranking of the Most Influential Persons in History, listsNumberOfPeople, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: listsNumberOfPeople Context triple: [The 100: A Ranking of the Most Influential Persons in History, listsNumberOfPeople, 100]
-
A.
peopleCountDescriptor
Indicates how the number of people involved in a situation, group, or context is characterized or described.
-
B.
numberOfNames
Indicates the count of distinct names associated with a given entity.
-
C.
populationCount
Indicates the total number of individuals in a specified group, area, or category.
-
D.
userCount
Indicates the number of users associated with or involved in a given context or entity.
-
E.
numberOfPersons
chosen
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb8a0b4881908ff27c5a75bd4a95 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76a84a081908d4184c55b728e48 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:58 p.m.