Triple
T15795208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian highlands |
E382959
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Racha |
E69941
|
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: Racha | Statement: [Georgian highlands, hasPart, Racha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Racha Context triple: [Georgian highlands, hasPart, Racha]
-
A.
Racha
chosen
Racha is a mountainous historical region in northwestern Georgia known for its scenic landscapes, traditional villages, and distinctive wines.
-
B.
Si Racha
Si Racha is a coastal city in eastern Thailand known for its industrial port, proximity to major tourist destinations, and as the namesake of the popular Sriracha chili sauce.
-
C.
Raka
Raka is an individual known primarily through their personal relationship with Koki.
-
D.
Raka
Raka is a renowned Afrikaans narrative poem by N. P. van Wyk Louw that explores themes of civilization, barbarism, and moral conflict through an allegorical tale.
-
E.
Ráquira
Ráquira is a Colombian town renowned for its traditional pottery, colorful handicrafts, and vibrant colonial architecture.
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4dc887081909d682ae153f06d97 |
completed | April 16, 2026, 10:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff90aea81c8190ad8bc0cdedf4b77a |
completed | May 9, 2026, 7:53 p.m. |
Created at: April 10, 2026, 4:48 a.m.