Triple
T13946075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tbilisi Aircraft Manufacturing |
E335387
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
TAM
TAM is a Georgian aerospace company based in Tbilisi that designs, manufactures, and services aircraft and related aviation components.
|
E1070521
|
NE FINISHED |
How this triple was built (4 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: [Tbilisi Aircraft Manufacturing, hasAbbreviation, TAM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TAM Context triple: [Tbilisi Aircraft Manufacturing, hasAbbreviation, TAM]
-
A.
TAM
TAM is the standard abbreviation used for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
-
B.
TAM
TAM is the former brand name and airline code of LATAM Airlines Brasil, one of Brazil’s largest commercial airlines.
-
C.
TAM
TAM is a prominent annual conference focused on science, skepticism, and critical thinking, originally organized by the James Randi Educational Foundation.
-
D.
TAMSE
TAMSE is an Argentine state-owned defense manufacturer best known for producing the TAM family of medium tanks and other armored vehicles.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TAM Triple: [Tbilisi Aircraft Manufacturing, hasAbbreviation, TAM]
Generated description
TAM is a Georgian aerospace company based in Tbilisi that designs, manufactures, and services aircraft and related aviation components.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TAM Target entity description: TAM is a Georgian aerospace company based in Tbilisi that designs, manufactures, and services aircraft and related aviation components.
-
A.
TAM
TAM is the standard abbreviation used for the Tampa Tarpons, a Minor League Baseball team based in Tampa, Florida.
-
B.
TAM
TAM is a prominent annual conference focused on science, skepticism, and critical thinking, originally organized by the James Randi Educational Foundation.
-
C.
TAM
TAM is the former brand name and airline code of LATAM Airlines Brasil, one of Brazil’s largest commercial airlines.
-
D.
TAMSE
TAMSE is an Argentine state-owned defense manufacturer best known for producing the TAM family of medium tanks and other armored vehicles.
-
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. chosen
Provenance (5 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e10f60c81908ee9636e85c070ff |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce903c5c8190b72d83a5b842ad70 |
completed | May 3, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69f9fd5d4abc8190aa10d9f1c9f7f9c9 |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fb14bfa2c081908381bb74f040c6c8 |
completed | May 6, 2026, 10:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.