Triple
T25684936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 Census of India |
E644040
|
entity |
| Predicate | femalePopulation |
P128793
|
FINISHED |
| Object | 587130731 |
—
|
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: 587130731 | Statement: [2011 Census of India, femalePopulation, 587130731]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: femalePopulation Context triple: [2011 Census of India, femalePopulation, 587130731]
-
A.
hasGenderRatioFemale
Indicates the proportion or percentage of females relative to the total population in the described group or context.
-
B.
femaleMass
Indicates that the subject has a mass value specifically associated with its female form or female population.
-
C.
femaleMember
Indicates that one entity is a member of a group or organization and is identified as female.
-
D.
memberCountFemale
chosen
Indicates the number of female members associated with a given group or entity.
-
E.
malePopulation
Indicates the number of male individuals within a specified population or group.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fb7c000c819094efdcbb23ebddae |
completed | May 2, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69f5afec3e94819080d9ba86cf8c866e |
completed | May 2, 2026, 8:03 a.m. |
Created at: April 21, 2026, 8:06 p.m.