Triple
T27255661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Applause |
E687605
|
entity |
| Predicate | LondonStar |
P162284
|
FINISHED |
| Object | Lauren Bacall |
—
|
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: Lauren Bacall | Statement: [Applause, LondonStar, Lauren Bacall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LondonStar Context triple: [Applause, LondonStar, Lauren Bacall]
-
A.
servesCentralLondon
Indicates that something provides service or access specifically to the Central London area.
-
B.
interchangeAtLondon
Indicates that an interchange or transfer occurs at London between different routes, services, or modes of transport.
-
C.
boroughStreet
Indicates a relationship where a specific street is located within or belongs to a particular borough.
-
D.
secondaryLondonTerminal
Indicates that a location serves as a secondary terminal in London associated with a primary London terminal for a given service or route.
-
E.
BigBenContains
Indicates that Big Ben spatially encloses or holds the referenced entity within its structure.
- 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_69ef35567e808190a94458cd44ebff0c |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f626b9862c819084ddb3eb47678bcb |
completed | May 2, 2026, 4:30 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f622a8fe7c819096e8a43db263a423 |
completed | May 2, 2026, 4:13 p.m. |
Created at: April 27, 2026, 10:49 a.m.