Triple
T16062383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hisar Lok Sabha constituency |
E389642
|
entity |
| Predicate | hasAssemblySegment |
P121483
|
FINISHED |
| Object | Ratia |
E1192060
|
NE 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: Ratia | Statement: [Hisar Lok Sabha constituency, hasAssemblySegment, Ratia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ratia Context triple: [Hisar Lok Sabha constituency, hasAssemblySegment, Ratia]
-
A.
Ratia
chosen
Ratia is a town and municipal council in the Fatehabad district of the Indian state of Haryana.
-
B.
Riasti
Riasti is a regional dialect of the Saraiki language spoken primarily in parts of southern Punjab, Pakistan.
-
C.
Ristolas
Ristolas is a small mountain commune in the Hautes-Alpes department of southeastern France, situated in the Queyras region near the Italian border.
-
D.
Vaali
Vaali is a 1999 Tamil psychological thriller film starring Ajith Kumar in dual roles, widely regarded as one of his breakthrough performances.
-
E.
Muonio
Muonio is a small municipality in Finnish Lapland known for its Arctic landscapes, outdoor tourism, and proximity to the Swedish border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e21a00f6808190a60939ef7ce727a7 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb8cca308190875432a5cf5f8616 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 4:57 a.m.