Triple
T3531020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hadoti |
E74659
|
entity |
| Predicate | hasHistoricCity |
P3786
|
FINISHED |
| Object | Baran |
E364481
|
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: Baran | Statement: [Hadoti, hasHistoricCity, Baran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baran Context triple: [Hadoti, hasHistoricCity, Baran]
-
A.
Baran
Baran is a surname most notably associated with Paul Baran, a pioneering engineer of packet-switched networks and early internet technology.
-
B.
Baran
chosen
Baran is a city in the Hadoti region of Rajasthan, India, known for its historical temples, forts, and proximity to natural attractions like waterfalls and wildlife sanctuaries.
-
C.
Barcha
Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
-
D.
Bara
Bara is a town in Pakistan’s Khyber District, known as a key settlement in the Khyber Pass region with strategic and commercial significance.
-
E.
Hazaragi
Hazaragi is a variety of Persian primarily spoken by the Hazara people of central Afghanistan and surrounding regions, distinguished by its unique phonology and significant Turkic and Mongolic influences.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc988ee081909c6b9d5eed0d2d6d |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bb8421b481908bda2b4f45714605 |
completed | March 13, 2026, 7:23 a.m. |
Created at: March 8, 2026, 3:19 p.m.