Triple
T3893623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Far North Line |
E88118
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Tain |
E127900
|
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: Tain | Statement: [Far North Line, serves, Tain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tain Context triple: [Far North Line, serves, Tain]
-
A.
Tain
chosen
Tain is a historic town in the Highlands of Scotland, known as one of the country’s oldest royal burghs and a regional administrative and judicial center.
-
B.
Tura
Tura is a prominent town in the Indian state of Meghalaya, serving as a major administrative, cultural, and economic center in the Garo Hills region.
-
C.
Tura
Tura is a district in southern Cairo, Egypt, historically known for its limestone quarries used in ancient Egyptian monuments.
-
D.
Terik
Terik is a Southern Nilotic language spoken by the Terik people of western Kenya, closely related to Nandi and other Kalenjin languages.
-
E.
The Turim
The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
- 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_69aed9466d548190939f5217a23ed4ac |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecce860c8190b16eca2e14f6544f |
completed | March 9, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c96ff648190b03807547930d51d |
completed | March 14, 2026, 8:30 a.m. |
Created at: March 9, 2026, 3:21 p.m.