Triple
T146816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Art of the Deal |
E3347
|
entity |
| Predicate | timeframeCovered |
P302
|
FINISHED |
| Object | Donald Trump’s early real estate career |
—
|
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: Donald Trump’s early real estate career | Statement: [The Art of the Deal, timeframeCovered, Donald Trump’s early real estate career]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeframeCovered Context triple: [The Art of the Deal, timeframeCovered, Donald Trump’s early real estate career]
-
A.
timePeriodCoveredTo
Indicates the span or duration of time that is encompassed, addressed, or relevant to a given subject or entity.
-
B.
timePeriod
chosen
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
C.
focusPeriod
Indicates the specific time span during which attention, activity, or analysis is concentrated on something.
-
D.
refersToPeriod
Indicates that one entity designates, references, or is associated with a specific time period or interval.
-
E.
time
Indicates a temporal relationship specifying when an event occurs or how entities are ordered or related in time.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.