Triple
T29051373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emily Thorne |
E735267
|
entity |
| Predicate | usesLegalNameOf |
P171013
|
FINISHED |
| Object | Amanda Clarke (originally) |
E199987
|
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 Clarke (originally) | Statement: [Emily Thorne, usesLegalNameOf, Amanda Clarke (originally)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLegalNameOf Context triple: [Emily Thorne, usesLegalNameOf, Amanda Clarke (originally)]
-
A.
usesNameForm
Indicates that one entity adopts or applies a particular standardized form or variant of a name associated with another entity.
-
B.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
-
C.
canBeLegalGivenName
Indicates that a given name satisfies the rules or conditions required to be considered legally valid.
-
D.
canName
Indicates that one entity has the ability or permission to assign or state the name of another entity.
-
E.
usesNicknameIn
Indicates that one entity refers to another entity by a specific nickname within a particular context or setting.
- F. None of above. chosen
Provenance (5 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_69f077e64b88819094d37bdbca8191b3 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2537a59e8c8190a25861bc81fa2db1 |
completed | June 7, 2026, 9:19 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 28, 2026, 10:08 a.m.