Triple
T3075982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angle Lake station |
E64137
|
entity |
| Predicate | fareSystem |
P395
|
FINISHED |
| Object | ORCA |
E211950
|
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: ORCA | Statement: [Angle Lake station, fareSystem, ORCA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ORCA Context triple: [Angle Lake station, fareSystem, ORCA]
-
A.
ORCA
chosen
ORCA is a regional smart transit card system used for paying fares across multiple public transportation agencies in the Puget Sound region of Washington State.
-
B.
Orcines
Orcines is a commune in central France’s Puy-de-Dôme department, known for its proximity to the Chaîne des Puys volcanic range.
-
C.
Orr
Orr is a surname of Scottish origin most famously associated with legendary Canadian ice hockey defenseman Bobby Orr.
-
D.
Orca (Quint's boat)
Orca is the small fishing boat owned by shark hunter Quint in the film "Jaws," used for the perilous hunt for the great white shark.
-
E.
ORC
ORC (Optimized Row Columnar) is a highly efficient, columnar storage file format commonly used in big data systems to enable fast analytics and compression.
- 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada150d8e08190bde5f68e800e8feb |
completed | March 8, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f889e7fc8190858845221998f321 |
completed | March 11, 2026, 11:19 p.m. |
Created at: March 8, 2026, 3:02 p.m.