Triple
T35144307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Easy Lover |
E1014777
|
entity |
| Predicate | singleSequenceNext |
P88827
|
FINISHED |
| Object | Walking on the Chinese Wall |
—
|
NE NERFINISHED |
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: Walking on the Chinese Wall | Statement: [Easy Lover, singleSequenceNext, Walking on the Chinese Wall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: singleSequenceNext Context triple: [Easy Lover, singleSequenceNext, Walking on the Chinese Wall]
-
A.
nextSingle
Indicates that one entity is the immediately following single item in a sequence or ordered set relative to another entity.
-
B.
nextInSeries
chosen
Indicates that one entity directly follows another in an ordered sequence or progression.
-
C.
sequenceWith
Indicates that one entity occurs in a specific order directly before or after another entity as part of a defined sequence.
-
D.
usesSequence
Indicates that one entity employs or relies on a specific ordered sequence of elements, steps, or events in performing an action or defining a relationship.
-
E.
sequenceBegins
Indicates that one sequence starts at the beginning of, or is the initial part of, another sequence.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:02 p.m.