Triple
T273656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Scherzer |
E5199
|
entity |
| Predicate | hasPhysicalCharacteristic |
P274
|
FINISHED |
| Object | heterochromia iridum |
—
|
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: heterochromia iridum | Statement: [Max Scherzer, hasPhysicalCharacteristic, heterochromia iridum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalCharacteristic Context triple: [Max Scherzer, hasPhysicalCharacteristic, heterochromia iridum]
-
A.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
C.
hasBeard
Indicates that one entity possesses or displays a beard.
-
D.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
E.
demographicCharacteristic
Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dd0a99c819089968a5400c58c5f |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7345c4819086c21710864a1b42 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.