Triple
T9123402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIP |
E218913
|
entity |
| Predicate | usedInTown |
P87209
|
FINISHED |
| Object | Lage |
E693910
|
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: Lage | Statement: [LIP, usedInTown, Lage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lage Context triple: [LIP, usedInTown, Lage]
-
A.
Lage
Lage is the surname of Carlos Lage Dávila, a prominent Cuban politician who served as Vice President of the Council of State and was considered a key figure in the country’s government in the early 2000s.
-
B.
Lage
chosen
Lage is a town in the Lippe district of North Rhine-Westphalia, Germany, known for its location in the Teutoburg Forest region.
-
C.
Lage Landen
Lage Landen is the historical Low Countries region in Western Europe, roughly encompassing present-day Belgium, the Netherlands, and Luxembourg.
-
D.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
E.
Londa
Londa is a town in the Indian state of Karnataka that serves as an important railway junction and gateway to the Western Ghats.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0308ff628819083f02bf71eb40c5b |
completed | April 3, 2026, 9:26 p.m. |
Created at: March 30, 2026, 7:17 p.m.