Triple
T4291073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Point Reyes Station |
E99591
|
entity |
| Predicate | originalName |
P65
|
FINISHED |
| Object |
Olema Station
Olema Station is the former name of the small coastal town now known as Point Reyes Station in Marin County, California.
|
E879613
|
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: Olema Station | Statement: [Point Reyes Station, originalName, Olema Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olema Station Context triple: [Point Reyes Station, originalName, Olema Station]
-
A.
Kecun Station
Kecun Station is a major interchange stop on the Guangzhou Metro system in Guangzhou, China.
-
B.
Senkawa Station
Senkawa Station is a subway station in Tokyo, Japan, serving passengers on the Tokyo Metro network.
-
C.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
D.
Naha Station
Naha Station is a major railway terminal in Naha, Okinawa, serving as a key transportation hub for the city and surrounding region.
-
E.
Tengachaya Station
Tengachaya Station is a railway station in Osaka, Japan, serving as a local transit hub connecting several urban neighborhoods and lines.
- 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: Olema Station Triple: [Point Reyes Station, originalName, Olema Station]
Generated description
Olema Station is the former name of the small coastal town now known as Point Reyes Station in Marin County, California.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Olema Station Target entity description: Olema Station is the former name of the small coastal town now known as Point Reyes Station in Marin County, California.
-
A.
Kecun Station
Kecun Station is a major interchange stop on the Guangzhou Metro system in Guangzhou, China.
-
B.
Senkawa Station
Senkawa Station is a subway station in Tokyo, Japan, serving passengers on the Tokyo Metro network.
-
C.
Nopo Station
Nopo Station is a major subway and bus terminal in Busan, South Korea, serving as a key transportation hub for the northeastern part of the city.
-
D.
Naha Station
Naha Station is a major railway terminal in Naha, Okinawa, serving as a key transportation hub for the city and surrounding region.
-
E.
Tengachaya Station
Tengachaya Station is a railway station in Osaka, Japan, serving as a local transit hub connecting several urban neighborhoods and lines.
- 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_69b3455175088190aa79c6e03b86647e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3507efb28819091a9d5b9161a5008 |
completed | March 12, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d98801deb8819092a45193078f09b4 |
completed | April 10, 2026, 11:30 p.m. |
| NEDg | Description generation | batch_69d98ae8403c81908a229aa06bd0388a |
completed | April 10, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98ce9ba0c8190a7c62fa670e23705 |
completed | April 10, 2026, 11:51 p.m. |
Created at: March 12, 2026, 11:08 p.m.