Triple
T2049849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Galicia |
E45539
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Lugo |
E191706
|
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: Lugo | Statement: [Kingdom of Galicia, capital, Lugo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lugo Context triple: [Kingdom of Galicia, capital, Lugo]
-
A.
Lugo
chosen
Lugo is a historic city in northwestern Spain known for its remarkably well-preserved Roman walls, a UNESCO World Heritage Site.
-
B.
Balvanera
Balvanera is a densely populated, traditionally working- and middle-class neighborhood in central Buenos Aires, Argentina, known for its historic architecture, commercial activity, and strong cultural life.
-
C.
Gavignano
Gavignano is a small Italian town in the Lazio region, historically notable as the birthplace of Pope Innocent III.
-
D.
Logudoro
Logudoro is a historical-cultural region in northern Sardinia known for its distinctive Sardinian dialect, medieval heritage, and rural landscapes.
-
E.
Neiva
Neiva is a major city in southwestern Colombia known as the economic and cultural center of the upper Magdalena River valley.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb98e10d48190bb96cd1f8ea3c08b |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae2007386481908b46c7bc2db8e4dd |
completed | March 9, 2026, 1:19 a.m. |
Created at: March 4, 2026, 7:39 p.m.