Triple
T7107792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Rosario |
E165629
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | TF |
E165630
|
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: TF | Statement: [El Rosario, vehicleRegistrationCode, TF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TF Context triple: [El Rosario, vehicleRegistrationCode, TF]
-
A.
TF
chosen
TF is the vehicle registration code used for motor vehicles registered in the Spanish province of Santa Cruz de Tenerife in the Canary Islands.
-
B.
TF
TF is the French abbreviation for the Federal Supreme Court of Switzerland, the country’s highest judicial authority.
-
C.
.tf
.tf is the country code top-level domain (ccTLD) designated for the French Southern and Antarctic Lands, an overseas territory of France.
-
D.
TFN
TFN is the IATA airport code for Tenerife North Airport, a major airport serving the island of Tenerife in Spain’s Canary Islands.
-
E.
FT
FT is the Faculty of Theology at the University of Geneva, a higher education institution specializing in theological and religious studies.
- 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_69c6888120f081908f8f01b201dc4a4c |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e5bbd4e481909e0948d01c6b15f4 |
completed | March 27, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79cb4840881908196e447618b38b0 |
completed | March 28, 2026, 9:17 a.m. |
Created at: March 27, 2026, 2:42 p.m.