Triple
T20876567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny Lane, Liverpool |
E514030
|
entity |
| Predicate | hasStreetSignTheftHistory |
P142214
|
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: [Penny Lane, Liverpool, hasStreetSignTheftHistory, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetSignTheftHistory Context triple: [Penny Lane, Liverpool, hasStreetSignTheftHistory, yes]
-
A.
locationOfInsigniaTheft
Indicates the place where the theft of an insignia occurred.
-
B.
theftStatus
Indicates the current state or condition of an entity with respect to being stolen, such as whether it has been reported, confirmed, or suspected as theft.
-
C.
hasRoadSign
Indicates that one entity possesses, displays, or is associated with a particular road sign.
-
D.
stolenDuring
Indicates that one entity was stolen in the course of, or at the time of, another specified event or time period.
-
E.
collectionBeforeTheft
Indicates that a collection or gathering of items occurred prior to the act of theft.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c6767ec0819080721e2e75bd0d66 |
completed | April 21, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a8dc148190b33ff51894e2a8f9 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:45 p.m.