Triple
T18180371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 United States Senate election in Pennsylvania |
E435263
|
entity |
| Predicate | wasBattlegroundRace |
P130767
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [2022 United States Senate election in Pennsylvania, wasBattlegroundRace, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasBattlegroundRace Context triple: [2022 United States Senate election in Pennsylvania, wasBattlegroundRace, true]
-
A.
battlegroundType
Indicates the specific kind or category of environment in which a battle or conflict takes place.
-
B.
wasKeyBattlegroundDuring
Indicates that a location served as an important site of conflict or struggle during a specified event or period.
-
C.
battledIn
Indicates that two or more entities engaged in a battle or conflict that took place at a specific location or during a particular event.
-
D.
battlefieldOf
Indicates that a location is the site where a particular battle or military engagement took place.
-
E.
battleWasPartOf
Indicates that a specific battle occurred as a component or phase within a larger military campaign, war, or conflict.
- 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dffa75a081908dad0dcbd736172d |
completed | April 19, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e4331e92408190ad607ba4956a3897 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:31 a.m.