Triple
T369041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Free City of Danzig |
E8226
|
entity |
| Predicate | hadOwnStamps |
P11714
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Free City of Danzig, hadOwnStamps, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadOwnStamps Context triple: [Free City of Danzig, hadOwnStamps, yes]
-
A.
hasPostNominal
Indicates that an entity is associated with a post-nominal title, abbreviation, or letters that follow a name to denote qualifications, honors, or status.
-
B.
hadMember
Indicates that an entity was formerly a member or part of another entity or group.
-
C.
hasSign
Indicates that an entity possesses, displays, or is associated with a particular sign or symbol.
-
D.
hasInsigniaWornBy
Indicates that a particular insignia is worn by a specified entity (such as a person, group, or organization).
-
E.
hadSpecialStatusIn
Indicates that an entity possessed a particular special, exceptional, or non-standard status within a specified context or time period.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebfdb0608190b1794a871d0d237a |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e95ede588190998fdf3a6ea90498 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0b23ec8190bef9d593162388a4 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.