Triple
T3962358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Basin |
E85933
|
entity |
| Predicate | extendsTo |
P1673
|
FINISHED |
| Object | Marlow |
E127996
|
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: Marlow | Statement: [London Basin, extendsTo, Marlow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marlow Context triple: [London Basin, extendsTo, Marlow]
-
A.
Marlow
chosen
Marlow is a historic English town on the River Thames in Buckinghamshire, known for its picturesque setting, suspension bridge, and literary associations.
-
B.
Conrad
Conrad is a character in Horace Walpole’s pioneering Gothic novel "The Castle of Otranto," whose fate helps set the story’s dark and supernatural events in motion.
-
C.
Conrad
Conrad is a masculine given name of Germanic origin, commonly used in various European countries and the English-speaking world.
-
D.
Kurtz
Kurtz is a surname of German origin borne by various notable individuals across fields such as philosophy, literature, and entertainment.
-
E.
Robinson
Robinson is a common English surname borne by numerous notable figures across politics, sports, arts, and other fields.
- 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_69aed93a96908190bcbdbfa718f155bd |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9617adc8190874b97a612fa7c72 |
completed | March 9, 2026, 4:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b533b8e00c819093af24f27eee793b |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:31 p.m.