Triple
T27028469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleepy Lagoon murder case |
E680851
|
entity |
| Predicate | racialAspect |
P59920
|
FINISHED |
| Object | anti-Mexican discrimination |
—
|
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: anti-Mexican discrimination | Statement: [Sleepy Lagoon murder case, racialAspect, anti-Mexican discrimination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racialAspect Context triple: [Sleepy Lagoon murder case, racialAspect, anti-Mexican discrimination]
-
A.
raceRole
Indicates the specific role, position, or function an entity holds within a race or racing event.
-
B.
racialIdentity
chosen
Indicates the relationship between an entity and the racial group or classification with which it is identified or categorized.
-
C.
relatedRace
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
-
D.
ethnicContrast
Indicates a relationship where two or more entities are contrasted or differentiated based on their ethnic backgrounds or identities.
-
E.
raceGroup
Indicates that the subject belongs to, or is categorized within, a particular racial or ethnic group.
- 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_69eeeb5566f08190813daf896fa3da04 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6223409688190959248db2146e527 |
completed | May 2, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 7:12 a.m.