Triple
T4192212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Time of the Doctor |
E89060
|
entity |
| Predicate | settingTimeSpan |
P302
|
FINISHED |
| Object | several centuries |
—
|
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: several centuries | Statement: [The Time of the Doctor, settingTimeSpan, several centuries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingTimeSpan Context triple: [The Time of the Doctor, settingTimeSpan, several centuries]
-
A.
timePeriod
chosen
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
B.
collectionTimespan
Indicates the time period over which a collection exists, is accumulated, or is considered valid.
-
C.
timePeriodWithin
Indicates that one time period is entirely contained within the bounds of another time period.
-
D.
timePeriodProposed
Indicates that a specific time period has been suggested or put forward for consideration or adoption.
-
E.
timePeriodCategory
Indicates the classification of a time period into a specific category or type (e.g., era, phase, or temporal grouping).
- 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_69aed9569a4481908b6c1fcec2a11e21 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af04b009dc8190abda3f149a5b16fa |
completed | March 9, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69af01935064819096b7619f42e164dd |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:46 p.m.