Triple
T5811294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sogdia |
E128872
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Kesh |
E334656
|
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: Kesh | Statement: [Sogdia, majorCity, Kesh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kesh Context triple: [Sogdia, majorCity, Kesh]
-
A.
Kesh
Kesh is the Sikh practice of maintaining uncut hair, symbolizing spiritual devotion and respect for the natural form given by God.
-
B.
Kesh
chosen
Kesh was a historic Central Asian city in present-day Uzbekistan, known as the birthplace of the conqueror Timur (Tamerlane).
-
C.
Keshi
Keshi is a horse-demon in Hindu mythology best known for being slain by the god Krishna (also called Kesava).
-
D.
Kes
Kes is a 1969 British drama film directed by Ken Loach, widely acclaimed for its realistic portrayal of a working-class boy in Northern England who finds solace in training a kestrel.
-
E.
Kes
Kes is an Ocampa crew member on Star Trek: Voyager, known for her short lifespan, strong empathic and telepathic abilities, and close relationships with Neelix and the Doctor.
- 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_69c0084788848190bcf71f6bc5d71597 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b54c2848190bb85212689d0b511 |
completed | March 22, 2026, 5:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09844f0b881908d4165e550f75d47 |
completed | March 23, 2026, 1:32 a.m. |
Created at: March 22, 2026, 3:52 p.m.