Triple
T31095113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lok Sabha constituency |
E792502
|
entity |
| Predicate | hasNumberInCountry |
P194710
|
FINISHED |
| Object | 543 elected constituencies |
—
|
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: 543 elected constituencies | Statement: [Lok Sabha constituency, hasNumberInCountry, 543 elected constituencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberInCountry Context triple: [Lok Sabha constituency, hasNumberInCountry, 543 elected constituencies]
-
A.
numericCountryCode
Indicates that a country is associated with a specific numeric code that uniquely identifies it.
-
B.
isCountryCode
Indicates that one entity is a valid country code designating the country represented by the other entity.
-
C.
hasAreaCodeCountry
Indicates that a particular telephone area code is associated with or belongs to a specific country.
-
D.
mobileNumbersHaveNoGeographicAreaCode
Indicates that mobile phone numbers are not associated with or constrained by any specific geographic area code.
-
E.
telephoneSystemCountry
Indicates that a telephone system operates within, or is associated with, a specific country.
- F. None of above. chosen
Provenance (4 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_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
| PDg | Predicate description generation | batch_69fd82ebe1c081908455fc45b6e45178 |
completed | May 8, 2026, 6:30 a.m. |
Created at: April 29, 2026, 9:03 p.m.