Triple
T9121619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N3 national route |
E218863
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Villiers |
E246028
|
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: Villiers | Statement: [N3 national route, passesThrough, Villiers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Villiers Context triple: [N3 national route, passesThrough, Villiers]
-
A.
Villiers
chosen
Villiers is a prominent English aristocratic surname historically associated with influential political figures and members of the nobility.
-
B.
Talbot
Talbot is a surname of English and Norman origin, historically associated with several notable families and individuals.
-
C.
Heydon
Heydon is a surname and place name of English origin, associated with various locations and families in the United Kingdom.
-
D.
Hailwood
Hailwood is the surname of legendary British motorcycle racer Mike Hailwood, widely regarded as one of the greatest riders in the history of the sport.
-
E.
Surtees
Surtees is an English surname historically associated with notable figures in British literature, motorsport, and regional history.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b32ba88190b2b4406c7b905cca |
completed | April 1, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0308ff628819083f02bf71eb40c5b |
completed | April 3, 2026, 9:26 p.m. |
Created at: March 30, 2026, 7:17 p.m.