Triple
T3608710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centro Region |
E76433
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Tomar |
E371690
|
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: Tomar | Statement: [Centro Region, containsCity, Tomar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomar Context triple: [Centro Region, containsCity, Tomar]
-
A.
Tomar
chosen
Tomar is a historic Portuguese city in the Santarém District, best known for its Templar-founded Convent of Christ, a UNESCO World Heritage site.
-
B.
Valdemoro
Valdemoro is a municipality and growing suburban town in central Spain, located south of Madrid.
-
C.
Majadahonda
Majadahonda is a suburban municipality west of Madrid, Spain, known for its residential character, shopping centers, and sports facilities.
-
D.
Andújar
Andújar is a historic town in the province of Jaén, Andalusia, Spain, known for its olive oil production and its location near the Sierra de Andújar Natural Park.
-
E.
Zamora
Zamora is a city in the Mexican state of Michoacán known for its agricultural production, colonial architecture, and religious landmarks such as the Cathedral of Our Lady of Guadalupe.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc22a3cf081908c20b6fb55be0db2 |
completed | March 8, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4330de7a08190933aa7e9dc0a65be |
completed | March 13, 2026, 3:53 p.m. |
Created at: March 8, 2026, 3:22 p.m.