Triple
T556171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Leipzig |
E11945
|
entity |
| Predicate | nameRestored |
P16337
|
FINISHED |
| Object | 1991 |
—
|
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: 1991 | Statement: [University of Leipzig, nameRestored, 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameRestored Context triple: [University of Leipzig, nameRestored, 1991]
-
A.
restoredBy
Indicates that an entity has been returned to a previous or improved state through the actions or intervention of another entity.
-
B.
restored
Indicates that an entity has returned another entity to a previous or improved state, condition, or position after damage, loss, or alteration.
-
C.
namedAfter
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
D.
formerName
Indicates that an entity was previously known by a different name in the past.
-
E.
realName
Indicates that one entity is the actual, full, or birth name of another entity, which may be known by an alias, nickname, or alternate identity.
- 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_69a4932941d08190815efd422f0b4ca7 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4991ef9b0819092ec0407270373f4 |
completed | March 1, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69a494bd78e8819083c519669158f209 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985952a481908b918350ececf484 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.