Triple
T3589203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyndon |
E75983
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Linden |
E156945
|
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: Linden | Statement: [Lyndon, relatedName, Linden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linden Context triple: [Lyndon, relatedName, Linden]
-
A.
Linden
Linden is a small village in the Dutch province of North Brabant, known for its rural character and location near the Maas River.
-
B.
Linden
chosen
Linden is a town in Lower Saxony, Germany, known as the birthplace of political theorist Hannah Arendt.
-
C.
Linwood
Linwood is a small Scottish town in Renfrewshire, near Paisley, known historically for its car manufacturing and as a residential commuter community for the Greater Glasgow area.
-
D.
Oakwood
Oakwood is a residential neighborhood on Staten Island, New York City, known for its suburban character and proximity to the island’s eastern shore.
-
E.
Orange Grove
Orange Grove is a historic public square in the city of Bath, England, known for its Georgian architecture and proximity to major landmarks like Bath Abbey.
- 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc13b2970819084181425b01f9595 |
completed | March 8, 2026, 6:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b40304a2e08190bcf25ddaf2bc5a2a |
completed | March 13, 2026, 12:28 p.m. |
Created at: March 8, 2026, 3:22 p.m.