Triple
T11278617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hertha BSC |
E267002
|
entity |
| Predicate | homeCityPopulationRankInGermany |
P25930
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Hertha BSC, homeCityPopulationRankInGermany, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCityPopulationRankInGermany Context triple: [Hertha BSC, homeCityPopulationRankInGermany, 1]
-
A.
rankAmongGermanStates
Indicates the relative position or standing of a German state when ordered or compared to other German states by a specific criterion (such as size, population, or performance).
-
B.
hasMunicipalAreaRankingInGermany
Indicates that a municipality holds a specific rank or position in comparison to other municipalities in Germany based on its area size.
-
C.
rankWithinGermanStates
Indicates the relative position or standing of an entity compared to others within the set of German federal states.
-
D.
rankInGermanyByArea
Indicates the position of an entity in an ordered list based on its area size within Germany.
-
E.
hasPopulationRankInRegion
chosen
Indicates that an entity has a specific population-based rank or position within a defined geographic region.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e967ebb4819080b09ed3cec44e77 |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:31 p.m.