Triple
T10786518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheohar district |
E254463
|
entity |
| Predicate | hasPredominantSettlementPattern |
P14278
|
FINISHED |
| Object | villages |
—
|
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: villages | Statement: [Sheohar district, hasPredominantSettlementPattern, villages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPredominantSettlementPattern Context triple: [Sheohar district, hasPredominantSettlementPattern, villages]
-
A.
hadPrimarySettlementPattern
Indicates that an entity exhibited or was characterized by a particular dominant form or arrangement of human settlement.
-
B.
humanSettlementType
chosen
Indicates the classification of a human settlement based on its form or function, such as village, town, or city.
-
C.
hasTraditionalSettlementType
Indicates that an entity is associated with a specific traditional or historically established type of human settlement (e.g., village, town, hamlet).
-
D.
hasPopulationConcentrationIn
Indicates that a population is densely or significantly clustered within a specified geographic area or region.
-
E.
populationPattern
Indicates how a population is distributed, structured, or changes over space or time in relation to other entities or conditions.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732d5422481908d7ab833c6cbc879 |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.