Triple
T27604641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippe Petit |
E700146
|
entity |
| Predicate | sentenceAlternative |
P162737
|
FINISHED |
| Object | ordered to perform for children in Central Park |
—
|
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: ordered to perform for children in Central Park | Statement: [Philippe Petit, sentenceAlternative, ordered to perform for children in Central Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sentenceAlternative Context triple: [Philippe Petit, sentenceAlternative, ordered to perform for children in Central Park]
-
A.
sentence
Indicates that one entity is a sentence that expresses, contains, or encodes information about another entity.
-
B.
sentenceModification
Indicates that one sentence alters, qualifies, or elaborates on the meaning, structure, or content of another sentence.
-
C.
sentenceOf
Indicates that one entity is a sentence that belongs to, is contained in, or is part of another larger text or document.
-
D.
sentenceType
Indicates the classification of a sentence according to its communicative function or structural type (e.g., question, statement, command).
-
E.
sentenceReduction
Indicates that a longer or more complex sentence has been shortened or simplified while preserving its essential meaning.
- F. None of above. chosen
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_69ef6a4e2e208190b63b7268f405785c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6309aa494819092c2b02bd6adaeb6 |
completed | May 2, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69f62c1921008190a62675a31f66a875 |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d14c24c81909e86678c1b5fd429 |
completed | May 2, 2026, 4:57 p.m. |
Created at: April 27, 2026, 2:09 p.m.