Triple
T787687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marilyn Monroe |
E16840
|
entity |
| Predicate | culturalIconOf |
P958
|
FINISHED |
| Object | 20th century American cinema |
—
|
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: 20th century American cinema | Statement: [Marilyn Monroe, culturalIconOf, 20th century American cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culturalIconOf Context triple: [Marilyn Monroe, culturalIconOf, 20th century American cinema]
-
A.
hasCulturalSignificanceFor
chosen
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
B.
citySymbolOf
Indicates that a particular city serves as an official symbol or emblem representing another entity, such as a region, organization, or concept.
-
C.
citySymbol
Indicates that one entity serves as the official symbol or emblem representing a particular city.
-
D.
countryRepresented
Indicates that one entity serves as the official representative (such as an athlete, diplomat, or delegate) of a specific country in a given context or event.
-
E.
isCelebratedIn
Indicates that an event, person, or occasion is honored, observed, or commemorated within a particular place, time, or context.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a78171908190a38a70274bfbebf9 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:38 p.m.