Triple
T22751674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamberí |
E562716
|
entity |
| Predicate | borderedByDistrict |
P224
|
FINISHED |
| Object | Tetuán |
—
|
NE NERFINISHED |
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: Tetuán | Statement: [Chamberí, borderedByDistrict, Tetuán]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tetuán Context triple: [Chamberí, borderedByDistrict, Tetuán]
-
A.
Tetuán
Tetuán is a station on the Madrid Metro network serving the Tetuán district in the north of Spain’s capital.
-
B.
Tetuan
Tetuan is a Barcelona Metro station on line 2 located beneath Plaça de Tetuan in the Eixample district of Barcelona, Spain.
-
C.
مدينة الدار البيضاء
مدينة الدار البيضاء هي أكبر مدن المغرب ومركزه الاقتصادي الرئيسي، تقع على ساحل المحيط الأطلسي وتشتهر بمينائها الحيوي ومعالمها الحديثة والتاريخية.
-
D.
Tetuán district of Madrid
chosen
The Tetuán district of Madrid is a diverse, traditionally working-class area in the city’s northwest, known for its multicultural population, dense urban fabric, and mix of historic and modern developments.
-
E.
El Azbakeya
El Azbakeya is a historic district in central Cairo known for its cultural landmarks, markets, and longstanding role as an urban hub of the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b9ac348190bff4dc470931f7e3 |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:24 p.m.