Triple
T9195823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Watson |
E220703
|
entity |
| Predicate | givesNicknamesTo |
P56896
|
FINISHED |
| Object | Megan Hipwell and Scott Hipwell |
—
|
LITERAL 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: Megan Hipwell and Scott Hipwell | Statement: [Rachel Watson, givesNicknamesTo, Megan Hipwell and Scott Hipwell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: givesNicknamesTo Context triple: [Rachel Watson, givesNicknamesTo, Megan Hipwell and Scott Hipwell]
-
A.
nicknamedFor
Indicates that one entity serves as the source, inspiration, or reason for another entity’s nickname.
-
B.
hasNicknamedEntityType
Indicates that an entity is associated with another entity type specifically in the role of being its nickname or informal name.
-
C.
hasAffectionateNicknameFor
chosen
Indicates that one entity uses or assigns a fond, affectionate, or endearing nickname to another entity.
-
D.
notableNickname
Indicates that one entity is a well-known or widely recognized nickname or moniker for another entity.
-
E.
series1Nickname
Indicates that one entity is used as a nickname or informal alternative name for another entity within the context of a first series.
- F. None of above.
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_69ca83e7ba70819088b74866d9da2c30 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd87c3a3c8190b60f19873ef6e1f8 |
completed | April 1, 2026, 8:34 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:25 p.m.