Triple
T8810215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tutzing |
E209639
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object | STA |
E219463
|
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: STA | Statement: [Tutzing, vehicleRegistrationCode, STA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: STA Context triple: [Tutzing, vehicleRegistrationCode, STA]
-
A.
STA
chosen
STA is the vehicle registration code for the district of Starnberg in Bavaria, Germany.
-
B.
STM
STM is the station code for Smithtown station, a Long Island Rail Road commuter rail stop in Smithtown, New York.
-
C.
STM
STM is the stock ticker symbol for STMicroelectronics, a major global semiconductor manufacturer.
-
D.
STM
STM is the public transit agency serving the city of Montreal, operating its bus and metro networks.
-
E.
ST
ST is the common abbreviation for Sound Transit, the regional public transit agency serving the Seattle metropolitan area in Washington State.
- 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_69ca8363f3308190a47e3f1ebd51f613 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fd69df4819091e9a7dad87265a4 |
completed | March 31, 2026, 11:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6faa5dbc819083ecfbbb261cbc44 |
completed | April 3, 2026, 7:43 a.m. |
Created at: March 30, 2026, 6:45 p.m.