Triple
T22665052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tata Martino |
E559761
|
entity |
| Predicate | playedFor |
P2170
|
FINISHED |
| Object | Lanús |
—
|
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: Lanús | Statement: [Tata Martino, playedFor, Lanús]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lanús Context triple: [Tata Martino, playedFor, Lanús]
-
A.
Lanús
chosen
Lanús is a city in the Greater Buenos Aires metropolitan area of Argentina, known as an important industrial and residential center and as the home of the football club Club Atlético Lanús.
-
B.
Morón
Morón is a city in the western part of the Greater Buenos Aires metropolitan area in Argentina, known as an important residential and commercial hub.
-
C.
Vicente López
Vicente López is a suburban partido (district) in the northern Greater Buenos Aires area of Argentina, known for its residential neighborhoods and riverside parks along the Río de la Plata.
-
D.
Barracas
Barracas is a traditional working-class neighborhood in Buenos Aires, Argentina, known for its historic architecture, industrial past, and strong local identity.
-
E.
Morón city
Morón city is an urban center in central Cuba known historically for its sugar industry and as a gateway to nearby northern cays and beach resorts.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781b3dbc8190a312843cf8c1bfc6 |
completed | April 29, 2026, 3:16 a.m. |
Created at: April 17, 2026, 3:08 p.m.