Triple
T31741205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rape of Ammu |
E810144
|
entity |
| Predicate | setWithinInstitution |
P49721
|
FINISHED |
| Object | police station |
—
|
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: police station | Statement: [Rape of Ammu, setWithinInstitution, police station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: setWithinInstitution Context triple: [Rape of Ammu, setWithinInstitution, police station]
-
A.
inInstitution
chosen
Indicates that an entity is located within, belongs to, or is formally associated with a particular institution.
-
B.
grantedByInstitution
Indicates that something (such as a status, permission, or resource) is conferred or authorized by an institution.
-
C.
includesInstitution
Indicates that one entity contains, encompasses, or has as a member a particular institution.
-
D.
containsInstitutionalArea
Indicates that one entity includes within its boundaries or scope an area designated for institutional use (such as educational, governmental, or similar facilities).
-
E.
impliesForInstitution
Indicates that one condition, rule, or statement logically leads to or necessitates another specifically within the context of an institution.
- 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_69f348e233cc819083b6695f70cd75d8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ab4924cc81909046f5cc06c146bf |
completed | May 3, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:25 p.m.