Triple
T14267036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clan MacLaren |
E353672
|
entity |
| Predicate | associatedFamilyName |
P4276
|
FINISHED |
| Object |
MacLaren
MacLaren is a Scottish surname historically linked to Clan MacLaren of the Scottish Highlands.
|
E1090303
|
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: MacLaren | Statement: [Clan MacLaren, associatedFamilyName, MacLaren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MacLaren Context triple: [Clan MacLaren, associatedFamilyName, MacLaren]
-
A.
McLaren Automotive
McLaren Automotive is a British high-performance sports car and supercar manufacturer renowned for its Formula 1–derived engineering and cutting-edge design.
-
B.
Aston Martin
Aston Martin is a British luxury sports car manufacturer renowned for its high-performance grand tourers and long association with the James Bond film franchise.
-
C.
Mercedes
Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
-
D.
Mercedes
Mercedes is a coastal municipality in the Philippine province of Camarines Norte known for its fishing industry and nearby island attractions.
-
E.
Mercedes
Mercedes is the given first name of the British former ballerina and television personality Darcey Bussell.
- 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: MacLaren Triple: [Clan MacLaren, associatedFamilyName, MacLaren]
Generated description
MacLaren is a Scottish surname historically linked to Clan MacLaren of the Scottish Highlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MacLaren Target entity description: MacLaren is a Scottish surname historically linked to Clan MacLaren of the Scottish Highlands.
-
A.
McLaren Automotive
McLaren Automotive is a British high-performance sports car and supercar manufacturer renowned for its Formula 1–derived engineering and cutting-edge design.
-
B.
Aston Martin
Aston Martin is a British luxury sports car manufacturer renowned for its high-performance grand tourers and long association with the James Bond film franchise.
-
C.
Mercedes
Mercedes is the given first name of the British former ballerina and television personality Darcey Bussell.
-
D.
Mercedes
Mercedes is a courageous and compassionate housekeeper who secretly aids the Spanish Maquis resistance in Guillermo del Toro’s dark fantasy film "Pan’s Labyrinth."
-
E.
Mercedes
Mercedes is a coastal municipality in the Philippine province of Camarines Norte known for its fishing industry and nearby island attractions.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6358c2288190ac1fd26e688a605d |
completed | April 14, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd326551b08190ae8fe220a6422339 |
completed | May 8, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69fd3417e8e88190b099bfe4ba30f364 |
completed | May 8, 2026, 12:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd37df3dfc8190a594abb2c14e11bb |
completed | May 8, 2026, 1:09 a.m. |
Created at: April 10, 2026, 1:09 a.m.