Triple
T14136414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guayas metropolitan area |
E350306
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Milagro |
E250930
|
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: Milagro | Statement: [Guayas metropolitan area, hasPart, Milagro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Milagro Context triple: [Guayas metropolitan area, hasPart, Milagro]
-
A.
Milagro
chosen
Milagro is a city in Ecuador known as an important agricultural and commercial center, particularly for sugarcane and rice production.
-
B.
Milagros
Milagros is a coastal municipality in the province of Masbate in the Philippines, known for its fishing communities and rural agricultural economy.
-
C.
Brazo Blest
Brazo Blest is a scenic western arm of Nahuel Huapi Lake in Argentine Patagonia, known for its lush forests, waterfalls, and access to the Andes near the Chilean border.
-
D.
Medalla Milagrosa
Medalla Milagrosa is a station on the Buenos Aires Underground, located in the city’s southeastern area and serving the Line E route.
-
E.
La Joya
La Joya is the nickname of Argentine footballer Paulo Dybala, highlighting his status as a highly skilled and valuable attacking player.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610fb86c81909eb26bf9c13696ca |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf14439c81908b2a9999a35cc346 |
completed | May 7, 2026, 6:51 p.m. |
Created at: April 10, 2026, 12:18 a.m.