Triple
T12791005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunnels Wood Industrial Area |
E305758
|
entity |
| Predicate | roadAccess |
P385
|
FINISHED |
| Object | A1(M) |
E160628
|
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: A1(M) | Statement: [Gunnels Wood Industrial Area, roadAccess, A1(M)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A1(M) Context triple: [Gunnels Wood Industrial Area, roadAccess, A1(M)]
-
A.
A1(M)
chosen
A1(M) is a series of motorway-standard sections in England that upgrade parts of the historic A1 route between London and the North.
-
B.
A-1
A-1 is the station code assigned to Kabaty, the southern terminus of Warsaw Metro Line M1.
-
C.
M1
M1 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across the city’s waters.
-
D.
M1
M1 is Budapest’s historic Millennium Underground line, one of the world’s oldest metro lines and a UNESCO World Heritage site.
-
E.
M1
M1 is the main primary mirror of the Extremely Large Telescope, responsible for collecting and focusing incoming light for its observations.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6b55248190ab938e69eb263612 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68508e4488190bb57a1ade93987ab |
completed | May 2, 2026, 11:13 p.m. |
Created at: April 9, 2026, 5:30 p.m.