Triple
T8719979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Bretagne |
E206986
|
entity |
| Predicate | parentOrganization |
P254
|
FINISHED |
| Object | TER |
E41185
|
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: TER | Statement: [TER Bretagne, parentOrganization, TER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TER Context triple: [TER Bretagne, parentOrganization, TER]
-
A.
TER
chosen
TER is a network of regional express trains in France that provides local passenger rail services across various regions.
-
B.
TER
TER is the IATA airport code for Lajes Airport on Terceira Island in the Azores, Portugal.
-
C.
Ter
The Ter is a river in northeastern Catalonia, Spain, that flows through cities such as Girona before emptying into the Mediterranean Sea.
-
D.
TR
TR is the postcode area covering Truro and much of Cornwall in southwest England.
-
E.
TR
TR is the two-letter ISO 3166-1 alpha-2 country code assigned to Turkey for international standardization and referencing.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d02a52c81909f93622ae6920b80 |
completed | March 31, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf42a3efa881908ffc5e1a257fd472 |
completed | April 3, 2026, 4:31 a.m. |
Created at: March 30, 2026, 6:36 p.m.