Triple
T38389917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Cree |
E899684
|
entity |
| Predicate | alternateWorkTitle |
P85265
|
FINISHED |
| Object | Dan Leno and the Limehouse Golem |
—
|
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: Dan Leno and the Limehouse Golem | Statement: [Elizabeth Cree, alternateWorkTitle, Dan Leno and the Limehouse Golem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternateWorkTitle Context triple: [Elizabeth Cree, alternateWorkTitle, Dan Leno and the Limehouse Golem]
-
A.
alternateWorkingTitle
chosen
Indicates that one title serves as an alternative working title for the same work or project as another title.
-
B.
aliasOfOccupation
Indicates that one occupation term is an alternative name or alias for another occupation.
-
C.
workTitle
Indicates the formal title or name of a work (such as a book, artwork, or composition) associated with an entity.
-
D.
workTitleIn
Indicates that one entity is the title of a work (e.g., book, film, artwork) that appears within or is contained in another entity.
-
E.
refersToWorkTitleAbbreviationOf
Indicates that one entity refers to a work by using an abbreviated form of that work’s title.
- 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_69f76e5c9b808190b486523f5c2f817d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.