Triple
T17101259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lady in the Lake |
E414984
|
entity |
| Predicate | hasDetectiveSeriesNumber |
P61667
|
FINISHED |
| Object | fourth Philip Marlowe novel |
—
|
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: fourth Philip Marlowe novel | Statement: [The Lady in the Lake, hasDetectiveSeriesNumber, fourth Philip Marlowe novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDetectiveSeriesNumber Context triple: [The Lady in the Lake, hasDetectiveSeriesNumber, fourth Philip Marlowe novel]
-
A.
hasSeriesNumber
chosen
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
-
B.
reporterSeriesNumber
Indicates the numerical designation of a particular series within a set of reports or reporter publications.
-
C.
designationSeries
Indicates that one designation belongs to or is part of a broader series of related designations.
-
D.
seriesNumberInCarryOn
Indicates that an item has a specific series or sequence number within a set of carry-on items.
-
E.
isNumberedBy
Indicates that an entity is assigned, identified, or organized by a specific number or numbering scheme.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc0182cc8190b8aa9c980f11ba57 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.