Triple
T14767737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beau Knapp |
E347042
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Beau |
E486254
|
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: Beau | Statement: [Beau Knapp, givenName, Beau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beau Context triple: [Beau Knapp, givenName, Beau]
-
A.
Beau
chosen
Beau is a masculine given name of French origin meaning "handsome" that is commonly used in English-speaking countries.
-
B.
Le Beau
Le Beau is a courtier in Shakespeare’s comedy "As You Like It," serving as a messenger and observer who reports on events at Duke Frederick’s court.
-
C.
Maddox
Maddox is the eldest son of actors Angelina Jolie and Brad Pitt, known for largely growing up in the public eye.
-
D.
Benji
Benji is a given name shared by various individuals, including historical and contemporary figures across different fields.
-
E.
Beyton
Beyton is a small rural village and civil parish in the English county of Suffolk, known for its traditional village green and historic buildings.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec81236f081908063bb4350b7b985 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf86730819082cf3f502ec16a46 |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:30 a.m.