Triple
T9565282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amanda Seyfried |
E230774
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Amanda |
E230773
|
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: Amanda | Statement: [Amanda Seyfried, givenName, Amanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amanda Context triple: [Amanda Seyfried, givenName, Amanda]
-
A.
Amanda
Amanda is the central character of the work "The Relapse," around whom the main events and conflicts of the story revolve.
-
B.
Amanda
chosen
Amanda is a feminine given name of Latin origin, meaning "worthy of love" or "lovable."
-
C.
Amanda
"Amanda" is a song by the American punk rock band Green Day from their album ¡Tré!.
-
D.
Amanda
Amanda is the central protagonist of the action-thriller film "Into the Blue," around whom the underwater treasure-hunting adventure revolves.
-
E.
Amanda
Amanda is the assumed identity of the main character Emily Thorne in the television series "Revenge."
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd996a01b081908e2782f41520f73d |
completed | April 1, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d152abb0788190ab2e204d9a082ccf |
completed | April 4, 2026, 6:04 p.m. |
Created at: March 30, 2026, 8:04 p.m.