Triple
T18479068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Man Who Loved Only Numbers |
E451509
|
entity |
| Predicate | timeInWork |
P32671
|
FINISHED |
| Object | 20th century |
—
|
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: 20th century | Statement: [The Man Who Loved Only Numbers, timeInWork, 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeInWork Context triple: [The Man Who Loved Only Numbers, timeInWork, 20th century]
-
A.
spentTimeIn
Indicates that an entity has spent a certain amount or period of time in a particular place or context.
-
B.
workPeriod
Indicates the span of time during which an entity is engaged in a particular work or employment activity.
-
C.
workLength
chosen
Indicates the duration or length of time associated with a particular work or task.
-
D.
timeStatus
Indicates the temporal state or condition of an event or entity relative to a reference time (e.g., past, present, future, ongoing, or scheduled).
-
E.
endTimeDetail
Indicates the specific or refined information about when an event, action, or state concludes.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53065e8388190bb216dae89f8cf75 |
completed | April 19, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69e469d671088190b619de96ea6f92ab |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:35 a.m.