Triple
T11357873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opovo municipality |
E269007
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Sakule |
E920934
|
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: Sakule | Statement: [Opovo municipality, hasVillage, Sakule]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sakule Context triple: [Opovo municipality, hasVillage, Sakule]
-
A.
Sakule
chosen
Sakule is a village located within the municipality of Opovo in Serbia, known as a small rural settlement in the Vojvodina region.
-
B.
Kasulu
Kasulu is a town in western Tanzania that serves as one of the main urban and commercial centers of the Kigoma Region.
-
C.
Khanke
Khanke is a village in northern Iraq’s Kurdistan Region, known for hosting large camps for internally displaced Yazidis who fled ISIS violence.
-
D.
Sakia
Sakia is a prominent cultural center and arts venue in Cairo, Egypt, known for hosting concerts, exhibitions, and a wide range of cultural events.
-
E.
Omaruru
Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea419afc8190b3a93141d015ebdf |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58b8d5f5c8190a80a52f2063bb5b0 |
completed | April 20, 2026, 2:12 a.m. |
Created at: April 8, 2026, 9:33 p.m.