Triple
T8796988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LATAM Brasil |
E209312
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | TAM |
E759594
|
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: TAM | Statement: [LATAM Brasil, callsign, TAM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TAM Context triple: [LATAM Brasil, callsign, TAM]
-
A.
TAM
TAM is a prominent annual conference focused on science, skepticism, and critical thinking, originally organized by the James Randi Educational Foundation.
-
B.
TAM
TAM is the standard abbreviation used for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
-
C.
TAM
chosen
TAM is the former brand name and airline code of LATAM Airlines Brasil, one of Brazil’s largest commercial airlines.
-
D.
TAD
TAD is the OECD’s Trade and Agriculture Directorate, which develops international policies and analysis on global trade, agriculture, and related economic issues.
-
E.
TAD
TAD is an acronym commonly used to refer to a Tax Allocation District, a designated area where future tax revenues are used to finance redevelopment and public improvements.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa370d08190885ef65e3a3e56d3 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf891583d48190ba276b5a1f7d6f7a |
completed | April 3, 2026, 9:32 a.m. |
Created at: March 30, 2026, 6:44 p.m.