Triple
T9831758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian indenture system |
E239001
|
entity |
| Predicate | numberOfPeopleInvolved |
P2307
|
FINISHED |
| Object | over 1 million |
—
|
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: over 1 million | Statement: [Indian indenture system, numberOfPeopleInvolved, over 1 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPeopleInvolved Context triple: [Indian indenture system, numberOfPeopleInvolved, over 1 million]
-
A.
numberOfPersons
chosen
Indicates the total count of individual persons associated with or involved in a given entity, event, or context.
-
B.
constantInvolved
Indicates that a constant participates in or is directly involved in the specified relation, operation, or context.
-
C.
hasPeopleInvolved
Indicates that certain people participate in, are associated with, or are otherwise involved in the referenced entity or event.
-
D.
numberOfPerpetrators
Indicates the count of distinct individuals who carried out or participated in a particular act, event, or offense.
-
E.
typeOfInvolvement
Indicates the specific role, capacity, or manner in which one entity is involved with or participates in another entity or activity.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb335623c8190902de29795bce87d |
completed | April 2, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cd03e30bc08190816c0a6d29c21b0f |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:32 p.m.