Triple
T19152900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | First inauguration of Abraham Lincoln |
E468852
|
entity |
| Predicate | attireOfPresident |
P134631
|
FINISHED |
| Object | black frock coat |
—
|
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: black frock coat | Statement: [First inauguration of Abraham Lincoln, attireOfPresident, black frock coat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attireOfPresident Context triple: [First inauguration of Abraham Lincoln, attireOfPresident, black frock coat]
-
A.
portraysUSPresident
Indicates that one entity depicts, represents, or plays the role of a U.S. President in some medium or context.
-
B.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
C.
associatedPresident
Indicates a relationship where a person, organization, event, or entity is linked or connected to a specific president in a relevant or significant way.
-
D.
presidentElect
Indicates that one entity has been elected to be president of another entity (such as a country or organization) but has not yet assumed the office.
-
E.
presidentialNumber
Indicates the ordinal position a person holds in a sequence of presidents (e.g., first, second, third president).
- 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb7575c8190b52a9d2bde5ac288 |
completed | April 20, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b475d88190a8c15e8eb01dbfef |
completed | April 19, 2026, 11:17 a.m. |
| PDg | Predicate description generation | batch_69e4bfe9ef7081908a74a57d1fc731ea |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 12:06 p.m.