Triple
T9414335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Calder |
E226976
|
entity |
| Predicate | hasNearbyVillage |
P4647
|
FINISHED |
| Object |
Woolfords
Woolfords is a small rural village in West Lothian, Scotland, situated near the town of West Calder.
|
E797526
|
NE FINISHED |
How this triple was built (4 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: Woolfords | Statement: [West Calder, hasNearbyVillage, Woolfords]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woolfords Context triple: [West Calder, hasNearbyVillage, Woolfords]
-
A.
Harlequin
Harlequin is a major publishing imprint best known for its extensive catalog of romance novels and commercial fiction.
-
B.
Harlequin
Harlequin is a classic comic servant character from the Italian commedia dell’arte tradition, known for his colorful diamond-patterned costume, acrobatic antics, and mischievous, witty personality.
-
C.
Lang & Witchell
Lang & Witchell was a prominent early 20th-century Dallas-based architectural firm known for designing significant commercial and civic buildings in Texas.
-
D.
Sarah Lancaster
Sarah Lancaster is an American actress best known for her television roles, including playing Ellie Bartowski on the series "Chuck."
-
E.
Jane Wolfe
Jane Wolfe was an American silent film actress best known for her early 20th-century screen roles and later association with occultist Aleister Crowley.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Woolfords Triple: [West Calder, hasNearbyVillage, Woolfords]
Generated description
Woolfords is a small rural village in West Lothian, Scotland, situated near the town of West Calder.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Woolfords Target entity description: Woolfords is a small rural village in West Lothian, Scotland, situated near the town of West Calder.
-
A.
Harlequin
Harlequin is a major publishing imprint best known for its extensive catalog of romance novels and commercial fiction.
-
B.
Harlequin
Harlequin is a classic comic servant character from the Italian commedia dell’arte tradition, known for his colorful diamond-patterned costume, acrobatic antics, and mischievous, witty personality.
-
C.
Lang & Witchell
Lang & Witchell was a prominent early 20th-century Dallas-based architectural firm known for designing significant commercial and civic buildings in Texas.
-
D.
Sarah Lancaster
Sarah Lancaster is an American actress best known for her television roles, including playing Ellie Bartowski on the series "Chuck."
-
E.
Jane Wolfe
Jane Wolfe was an American silent film actress best known for her early 20th-century screen roles and later association with occultist Aleister Crowley.
- F. None of above. chosen
Provenance (5 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c7bd648190b17f082883c98239 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107b63cf48190a072e3434a7b85a8 |
completed | April 4, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_69d108466fb481909682fcaac354b312 |
completed | April 4, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d108be82888190b0ec08119cd00b68 |
completed | April 4, 2026, 12:49 p.m. |
Created at: March 30, 2026, 7:47 p.m.