Triple
T25684950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 Census of India |
E644040
|
entity |
| Predicate | stateWithHighestPopulationDensity |
P30673
|
FINISHED |
| Object | Bihar |
—
|
NE NERFINISHED |
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: Bihar | Statement: [2011 Census of India, stateWithHighestPopulationDensity, Bihar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateWithHighestPopulationDensity Context triple: [2011 Census of India, stateWithHighestPopulationDensity, Bihar]
-
A.
hasHigherPopulationDensityThan
Indicates that the first entity has a greater number of inhabitants per unit area than the second entity.
-
B.
hasHighestUrbanizationRateIn
Indicates that the subject has the greatest proportion of its population living in urban areas compared to all other entities within the specified object region or group.
-
C.
isMostDenselyPopulatedCountryIn
Indicates that a country has the highest population density among all countries within a specified region or set.
-
D.
isOneOfMostDenselyPopulatedAreasIn
Indicates that an area ranks among the locations with the highest population density within a specified region or context.
-
E.
isMostDenselyPopulatedRegionIn
chosen
Indicates that a region has the highest population density compared to all other regions within a specified larger area 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 21, 2026, 8:06 p.m.