Triple
T36018796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial City of Giengen |
E1041924
|
entity |
| Predicate | todayKnownAs |
P22915
|
FINISHED |
| Object | Giengen an der Brenz |
—
|
NE NERFINISHED |
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: Giengen an der Brenz | Statement: [Imperial City of Giengen, todayKnownAs, Giengen an der Brenz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: todayKnownAs Context triple: [Imperial City of Giengen, todayKnownAs, Giengen an der Brenz]
-
A.
laterBecameKnownAs
Indicates that an entity was previously known by one name or identity and, at a later time, came to be known by a different name or identity.
-
B.
cityNowKnownAs
chosen
Indicates that a city has changed its name and specifies the new name it is currently known by.
-
C.
historicallyRecognizedAs
Indicates that an entity has been acknowledged or designated under a particular name, status, or role during a past historical period.
-
D.
knewAs
Indicates that one entity was acquainted with or recognized another entity under a particular identity, name, or role.
-
E.
knownAsBy
Indicates that one entity is referred to or recognized by another entity using a particular name or designation.
- 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_69f76e2b981881908e4e160607fa82eb |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ace165e48190ba026e09b68e0a83 |
completed | May 3, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.