Triple
T24380441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Traveler |
E614593
|
entity |
| Predicate | hasSubjectMatterCharacteristic |
P99469
|
FINISHED |
| Object | urban modernity |
—
|
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: urban modernity | Statement: [The Traveler, hasSubjectMatterCharacteristic, urban modernity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectMatterCharacteristic Context triple: [The Traveler, hasSubjectMatterCharacteristic, urban modernity]
-
A.
subjectHasCharacteristic
chosen
Indicates that a subject possesses, exhibits, or is defined by a particular characteristic or attribute.
-
B.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
-
C.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
D.
hasCourseCharacteristic
Indicates that a course possesses or is associated with a particular characteristic, feature, or attribute.
-
E.
subjectMatter
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
- 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_69e2d7e362e481909e32fe4ef8269d4f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293db31c481908484ab28921cd5fd |
completed | April 29, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:03 a.m.