Triple
T2818488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aragonese florin |
E54347
|
entity |
| Predicate | circulationArea |
P82
|
FINISHED |
| Object | Valencia |
E13494
|
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: Valencia | Statement: [Aragonese florin, circulationArea, Valencia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valencia Context triple: [Aragonese florin, circulationArea, Valencia]
-
A.
Valencia
chosen
Valencia is a major Spanish coastal city known for its historic architecture, vibrant culture, and significant role as a key Mediterranean trade and tourism hub.
-
B.
Valencia
Valencia is a municipality in the Philippine province of Negros Oriental known for its cool climate, geothermal energy resources, and natural attractions such as waterfalls and mountain landscapes.
-
C.
Valencia
Valencia is a major industrial and commercial city in north-central Venezuela and the capital of Carabobo state.
-
D.
Alicante
Alicante is a historic Mediterranean port city in southeastern Spain known for its beaches, castle-topped hill, and role as a major tourist and commercial center.
-
E.
Malaga
Malaga is a white wine grape variety name historically used as a synonym for Sémillon in certain wine-growing regions.
- 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_69ab49de0af08190b3da69683be1e728 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde6c44d881909f8275b6466e2f20 |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38ba5bc088190bd656c2959cdfb6a |
completed | March 13, 2026, 3:59 a.m. |
Created at: March 6, 2026, 9:59 p.m.