Triple
T28841230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Illinois's 1st congressional district |
E728318
|
entity |
| Predicate | hasPoliticalReputation |
P5316
|
FINISHED |
| Object | safe Democratic seat |
—
|
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: safe Democratic seat | Statement: [Illinois's 1st congressional district, hasPoliticalReputation, safe Democratic seat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliticalReputation Context triple: [Illinois's 1st congressional district, hasPoliticalReputation, safe Democratic seat]
-
A.
hasPoliticalCharacteristic
chosen
Indicates that an entity possesses a specific political attribute, quality, or affiliation.
-
B.
hasNotableReputation
Indicates that an entity is widely recognized or distinguished for a particular quality, achievement, or characteristic.
-
C.
domesticReputation
Indicates the level or nature of how an entity is regarded or perceived within its own country or internal context.
-
D.
refersToPersonReputation
Indicates that something is about, concerns, or makes reference to a particular person's reputation.
-
E.
hasReputationAmong
Indicates that an entity is regarded or perceived in a particular way by a specified group or audience.
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: April 28, 2026, 6:40 a.m.