Triple
T33877517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brontë Way |
E868394
|
entity |
| Predicate | hasEndingArea |
P47075
|
FINISHED |
| Object | near Wycoller area (approximate) |
—
|
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: near Wycoller area (approximate) | Statement: [Brontë Way, hasEndingArea, near Wycoller area (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEndingArea Context triple: [Brontë Way, hasEndingArea, near Wycoller area (approximate)]
-
A.
hasFinalArea
Indicates that an entity is associated with a specific area value representing its final or resulting size after some process or transformation.
-
B.
hasAreaTotal
Indicates the total surface area associated with an entity, typically measured over its entire extent.
-
C.
hasAreaRange
Indicates that something’s area falls within a specified minimum-to-maximum range.
-
D.
finishingArea
chosen
Indicates the location or area where an activity, process, or event comes to an end or is completed.
-
E.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
- 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_69f34995b81c8190acdb45cea5a10eff |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
Created at: May 1, 2026, 1:48 a.m.