Triple
T9139470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TAO |
E219285
|
entity |
| Predicate | assignedTo |
P3151
|
FINISHED |
| Object | Aeromar |
E42352
|
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: Aeromar | Statement: [TAO, assignedTo, Aeromar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aeromar Context triple: [TAO, assignedTo, Aeromar]
-
A.
Aeromar
chosen
Aeromar is a Mexican regional airline that primarily operates domestic and short-haul international flights, with a major operational base in Mexico City.
-
B.
Palmesana
Palmesana is the term used to refer to a female inhabitant or native of Palma de Mallorca, a city on the Spanish island of Mallorca.
-
C.
Taganga
Taganga is a small fishing village and popular backpacker destination on Colombia’s Caribbean coast, known for its beaches, diving, and proximity to Tayrona National Natural Park.
-
D.
Nauta
Nauta is a small river port town in Peru’s Loreto region, serving as a key gateway for tourism and access to the Pacaya-Samiria National Reserve in the Amazon rainforest.
-
E.
Navigo
Navigo is the contactless smart card ticketing system used for public transportation across the Île-de-France region, including Paris.
- 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_69ca83e012288190a5771058adbaabd2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8f129c08190b6f053984cb7363f |
completed | April 1, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0480458348190b0b87f7a66d85b87 |
completed | April 3, 2026, 11:06 p.m. |
Created at: March 30, 2026, 7:19 p.m.