Triple
T10971765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laurie Laurence |
E259251
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | Mr. Laurence |
E492797
|
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: Mr. Laurence | Statement: [Laurie Laurence, hasRelative, Mr. Laurence]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Laurence Context triple: [Laurie Laurence, hasRelative, Mr. Laurence]
-
A.
Mr. Laurence
chosen
Mr. Laurence is the wealthy, elderly neighbor and guardian of Laurie in Louisa May Alcott’s novel "Little Women."
-
B.
Rob Bhaer
Rob Bhaer is the younger son of Jo March and Professor Friedrich Bhaer in Louisa May Alcott’s "Little Women" series.
-
C.
Laurence
Laurence is a masculine given name of Latin origin, commonly used in English-speaking countries.
-
D.
Laurence
Laurence is one of the central characters in Mike Leigh’s play and film "Abigail’s Party," typically portrayed as a tense, status-conscious suburban husband.
-
E.
Mr. White
Mr. White is a seasoned, professional criminal and one of the central heist participants in Quentin Tarantino’s film "Reservoir Dogs," known for his conflicted morality and protective attitude toward Mr. Orange.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7719b5edc81908c1019f81e78bd2e |
completed | April 9, 2026, 9:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d790df108190b4a3a6fece372778 |
completed | April 18, 2026, 1 a.m. |
Created at: April 8, 2026, 9:24 p.m.