Triple
T21497116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvard school of antitrust |
E530383
|
entity |
| Predicate | viewsAsIndicatorOfConcern |
P102849
|
FINISHED |
| Object | high market concentration |
—
|
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: high market concentration | Statement: [Harvard school of antitrust, viewsAsIndicatorOfConcern, high market concentration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewsAsIndicatorOfConcern Context triple: [Harvard school of antitrust, viewsAsIndicatorOfConcern, high market concentration]
-
A.
concernedSee
Indicates that one entity looks at or observes another with a sense of worry, care, or concern.
-
B.
concernsDisplay
Indicates a relationship where something is about, relates to, or addresses the way something is shown or presented (its display).
-
C.
raisedConcernAbout
Indicates that one entity has expressed worry, doubt, or objection regarding another entity or issue.
-
D.
viewsBehaviorAs
Indicates that one entity interprets, judges, or regards another entity’s behavior in a particular way.
-
E.
viewsAs
chosen
Indicates that one entity perceives, interprets, or regards another entity in a particular way or role.
- 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea58faa08190ab9f60b0db3c425b |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:23 p.m.