Triple
T12044439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Anscombe |
E286748
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Intention |
E286749
|
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: Intention | Statement: [Elizabeth Anscombe, notableWork, Intention]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Intention Context triple: [Elizabeth Anscombe, notableWork, Intention]
-
A.
Intention
chosen
Intention is a highly influential 1957 philosophical work by Elizabeth Anscombe that reshaped contemporary debates about action, intention, and practical reasoning.
-
B.
Intentions
"Intentions" is a 2020 pop single by Justin Bieber featuring Quavo, known for its melodic hook and uplifting lyrics about appreciating a romantic partner.
-
C.
Good Intentions
Good Intentions is a popular song by British rapper and singer Nav, known for its melodic trap sound and introspective lyrics.
-
D.
Intentions of Murder
Intentions of Murder is a 1964 Japanese drama film by director Shohei Imamura that explores the life of an oppressed rural woman through a gritty, psychologically complex lens.
-
E.
Intuition
Intuition is the graphical user interface system of Amiga computers, responsible for managing windows, screens, gadgets, and user interaction.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9041fe3b0819094b82a6b17ac59c3 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49db574bc8190a0f2f858a2ff788d |
completed | May 1, 2026, 12:33 p.m. |
Created at: April 8, 2026, 9:47 p.m.