Triple
T31095091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lok Sabha constituency |
E792502
|
entity |
| Predicate | representationInBody |
P90996
|
FINISHED |
| Object | Lok Sabha |
—
|
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: Lok Sabha | Statement: [Lok Sabha constituency, representationInBody, Lok Sabha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representationInBody Context triple: [Lok Sabha constituency, representationInBody, Lok Sabha]
-
A.
representedBody
Indicates that one entity serves as a symbolic, artistic, or conceptual depiction of another entity’s body or physical form.
-
B.
representsInBody
Indicates that something is depicted, expressed, or manifested within the physical body of an entity.
-
C.
representationIn
chosen
Indicates that one entity serves as a depiction, model, or stand-in for another entity within a given context or medium.
-
D.
representation
Indicates that one entity stands in for, symbolizes, or depicts another entity in some context.
-
E.
hasRepresentationBody
Indicates that an entity is associated with a specific representational content or body that expresses or encodes it.
- 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_69f224cf157c81909e2d2bd88c9282c3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fdf5d05cc481909ec9e1b1f0784279 |
completed | May 8, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69fdf0cdd6948190838864ab3120dfa6 |
completed | May 8, 2026, 2:18 p.m. |
Created at: April 29, 2026, 9:03 p.m.