Triple
T32029970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teck |
E817927
|
entity |
| Predicate | lostGermanTitles |
P173140
|
FINISHED |
| Object | during World War I anti-German sentiment in Britain |
—
|
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: during World War I anti-German sentiment in Britain | Statement: [Teck, lostGermanTitles, during World War I anti-German sentiment in Britain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lostGermanTitles Context triple: [Teck, lostGermanTitles, during World War I anti-German sentiment in Britain]
-
A.
lostBritishTitles
Indicates that an entity has had its British titles removed, revoked, or otherwise ceased to hold them.
-
B.
hasTitleInGerman
Indicates that an entity has a specific title or name expressed in the German language.
-
C.
GermanLoss
Indicates that Germany experiences a loss, defeat, or negative outcome in the specified context or event.
-
D.
oneOfGermanys
Indicates that something or someone belongs to the set of entities that are part of, originate from, or are associated with Germany.
-
E.
numberOfGermanChampionships
Indicates the count of German championship titles associated with a given 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_69f348fbc8148190b3c0f95d4772b153 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: May 1, 2026, 12:18 a.m.