Triple
T17108905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyaur Kala |
E415172
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Erk Kala |
E415171
|
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: Erk Kala | Statement: [Gyaur Kala, near, Erk Kala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erk Kala Context triple: [Gyaur Kala, near, Erk Kala]
-
A.
Erk Kala
chosen
Erk Kala is an ancient fortified citadel forming the oldest core of the archaeological site of Merv in present-day Turkmenistan.
-
B.
Kalyar
Kalyar is a notable Sufi pilgrimage town in India associated with the Chishti Order and revered for its prominent dargah (shrine).
-
C.
Kalamian
Kalamian is the Glottolog-recognized name for a group of closely related Austronesian languages spoken in the Calamian Islands of the Philippines.
-
D.
Kalkan
Kalkan is a picturesque seaside town on Turkey’s Mediterranean coast, known for its historic architecture, steep cobbled streets, and upscale tourism.
-
E.
Khashuri
Khashuri is a town in central Georgia that serves as an important regional transport hub and gateway between eastern and western parts of the country.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2906a081909d0d43cf04319f52 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a03e2e48190a0b631dd8f6f8a24 |
completed | May 11, 2026, 2:08 a.m. |
Created at: April 10, 2026, 5:35 a.m.