Triple
T29980128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarangan Lake |
E761562
|
entity |
| Predicate | hasNearestLargeCity |
P112043
|
FINISHED |
| Object | Madiun |
—
|
NE NERFINISHED |
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: Madiun | Statement: [Sarangan Lake, hasNearestLargeCity, Madiun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearestLargeCity Context triple: [Sarangan Lake, hasNearestLargeCity, Madiun]
-
A.
largestNearbyCity
Indicates that one city is the largest (by population, area, or another defined metric) among the cities located within a specified nearby region of another place or city.
-
B.
nearestMajorCity
Indicates that one city is the closest significant urban center to another location or city compared to all other major cities.
-
C.
nearestLargeUrbanArea
chosen
Indicates that one entity is the closest major city or large urban center to the other entity.
-
D.
nearestSmallCity
Indicates that one city is the closest small-sized city in distance or proximity to another specified location or entity.
-
E.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
- F. None of above.
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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fe7b1c506c8190869c1a22031e0571 |
completed | May 9, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69fe796b2bdc8190a86980d44008f875 |
completed | May 9, 2026, 12:01 a.m. |
Created at: April 29, 2026, 6:34 p.m.