Triple
T4355979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph M. Schenck |
E98148
|
entity |
| Predicate | servedTimeAt |
P55738
|
FINISHED |
| Object | federal prison |
—
|
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: federal prison | Statement: [Joseph M. Schenck, servedTimeAt, federal prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servedTimeAt Context triple: [Joseph M. Schenck, servedTimeAt, federal prison]
-
A.
servedUntil
Indicates the ending time or date up to which an entity held a position, role, or service.
-
B.
servedDuring
Indicates that one entity held a role, position, or performed a function within the time period defined by another entity.
-
C.
servesLineSince
Indicates that a transportation service or route has been operating on a particular line since a specified point in time.
-
D.
isServedAt
Indicates that something (such as food, drink, or a service) is provided or made available at a particular place or venue.
-
E.
served
Indicates that one entity provided a service, assistance, or role-based function to or for another entity.
- F. None of above. chosen
Provenance (4 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351c5773481908446d84897e7a533 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:16 p.m.