Triple
T17108627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beauchamp Duff |
E415166
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Beauchamp |
E999052
|
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: Beauchamp | Statement: [Beauchamp Duff, givenName, Beauchamp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beauchamp Context triple: [Beauchamp Duff, givenName, Beauchamp]
-
A.
Beauchamp
Beauchamp is a commune in the northern suburbs of Paris, France, known for its residential character and proximity to other Val-d'Oise towns like Taverny.
-
B.
Beauchamp
chosen
Beauchamp is an English noble family name historically associated with medieval aristocracy and influential landholding lineages.
-
C.
Beauclerc
Beauclerc is the epithet of King Henry I of England, highlighting his reputation for learning and scholarly interests.
-
D.
Fitzwilly
Fitzwilly is a 1967 comedy film starring Dick Van Dyke as a butler who masterminds elaborate thefts to support his employer’s fading fortune.
-
E.
Beauchamp Duff
Beauchamp Duff was a British Indian Army general who served as Commander-in-Chief in India during the early years of the First World War.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2906a081909d0d43cf04319f52 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a03e2e48190a0b631dd8f6f8a24 |
completed | May 11, 2026, 2:08 a.m. |
Created at: April 10, 2026, 5:35 a.m.