Triple
T18078600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kattankudy |
E432624
|
entity |
| Predicate | religiousInstitutionDensity |
P95507
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Kattankudy, religiousInstitutionDensity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousInstitutionDensity Context triple: [Kattankudy, religiousInstitutionDensity, high]
-
A.
religiousInstitutionShared
Indicates that two entities are associated with or participate in the same religious institution or organization.
-
B.
hasReligiousBuildingDensity
chosen
Indicates the degree to which religious buildings are concentrated within a given area or region.
-
C.
isMajorReligiousInstitutionIn
Indicates that a major religious institution (such as a church, mosque, temple, or similar body) is located within or primarily based in a specified place or region.
-
D.
religiousBuildingCount
Indicates the number of religious buildings associated with or present in a given context or entity.
-
E.
religiousEnvironment
Indicates the religious context, atmosphere, or setting in which an entity exists or an action takes place.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9f6a85481909894c39c8be98d5d |
completed | April 19, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69e3f90c652481908133a73106d78919 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:27 a.m.