Triple
T4743775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Acre, London |
E105310
|
entity |
| Predicate | hasNotableJunction |
P1018
|
FINISHED |
| Object | junction with Garrick Street |
—
|
LITERAL 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: junction with Garrick Street | Statement: [Long Acre, London, hasNotableJunction, junction with Garrick Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableJunction Context triple: [Long Acre, London, hasNotableJunction, junction with Garrick Street]
-
A.
hasJunctionWith
chosen
Indicates that one entity meets or intersects with another at a shared junction point.
-
B.
hasJunctionIn
Indicates that one entity contains or includes a junction located within the spatial or structural extent of another entity.
-
C.
hasJunctionNumber
Indicates that a road, route, or similar pathway is assigned a specific junction or exit number.
-
D.
hasJunctionCount
Indicates the number of junctions associated with or contained in a given entity.
-
E.
isNumberedJunctionOf
Indicates that a junction (such as a road or rail intersection) has been assigned an official identifying number within a network.
- F. None of above.
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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64a85e9c81908e9c7bbbb998953e |
completed | March 20, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.