Triple
T33035121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley #5 |
E845285
|
entity |
| Predicate | hasCommonThemesWith |
P182877
|
FINISHED |
| Object | Berkeley #1 |
E845285
|
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: Berkeley #1 | Statement: [Berkeley #5, hasCommonThemesWith, Berkeley #1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonThemesWith Context triple: [Berkeley #5, hasCommonThemesWith, Berkeley #1]
-
A.
hasThematicSimilarityTo
chosen
Indicates that two entities share related themes, topics, or conceptual content to a notable degree.
-
B.
hasRelationshipTheme
Indicates that a relationship is characterized by, centered around, or thematically associated with a particular concept or subject.
-
C.
hasOverlappingInterestsFrom
Indicates that one entity shares some, but not necessarily all, interests in common with another entity, such that their sets of interests partially overlap.
-
D.
sharesMotifsWith
Indicates that two entities contain or employ similar recurring themes, patterns, or symbolic elements.
-
E.
commonIn
Indicates that something frequently occurs, appears, or is found within a specified context, group, or environment.
- F. None of above.
Provenance (4 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_69f34951348c8190b56746b0a7018182 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34e51034a88190b09e2fb61a4afe54 |
completed | June 19, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:24 a.m.