Triple
T14630193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Nájera |
E343460
|
entity |
| Predicate | place |
P373
|
FINISHED |
| Object | Nájera |
E627387
|
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: Nájera | Statement: [Battle of Nájera, place, Nájera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nájera Context triple: [Battle of Nájera, place, Nájera]
-
A.
Nájera
chosen
Nájera is a historic town in northern Spain known for its medieval heritage and role as a former capital of the Kingdom of Navarre.
-
B.
Almansa
Almansa is a historic town in the province of Albacete, Spain, known for its imposing medieval castle and its role as the site of a major battle in the War of the Spanish Succession.
-
C.
Calatayud
Calatayud is a historic town in northeastern Spain known for its Mudéjar architecture and strategic location along the Jalón River.
-
D.
Madarihat
Madarihat is a small town in West Bengal, India, known primarily as the main gateway and service hub for visitors to Jaldapara National Park.
-
E.
Daroca
Daroca is a historic fortified town in northeastern Spain known for its medieval walls, towers, and well-preserved old quarter.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a912248190a3df7f821395c776 |
completed | April 14, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5d0514081908c2bdc4fb77b1a7a |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:26 a.m.