Triple
T558933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time Europe |
E13404
|
entity |
| Predicate | hasOriginalContent |
P640
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Time Europe, hasOriginalContent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalContent Context triple: [Time Europe, hasOriginalContent, yes]
-
A.
hasOriginIn
Indicates that something begins, arises, or is derived from a specified source, place, or cause.
-
B.
hasSurvivingOriginals
Indicates that some of the original instances or versions of an entity still exist and have not been lost, destroyed, or replaced.
-
C.
hasInitial
Indicates that one entity possesses or is associated with the first letter or starting character of another entity’s name or value.
-
D.
originalText
Indicates that one text is the initial, unmodified version from which other versions, translations, or representations are derived.
-
E.
hasContentType
chosen
Indicates that an entity is associated with or classified by a specific type of content.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a499df43f08190b514a38d36fc271d |
completed | March 1, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.