Triple
T35976381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Barbara Cemetery |
E1040429
|
entity |
| Predicate | hasNotableBurial |
P196
|
FINISHED |
| Object |
Thomas M. Storke
Thomas M. Storke was an American newspaper publisher and politician from Santa Barbara, California, known for his long-time leadership of the Santa Barbara News-Press and his influence on local and state politics.
|
E2294778
|
NE 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: Thomas M. Storke | Statement: [Santa Barbara Cemetery, hasNotableBurial, Thomas M. Storke]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Thomas M. Storke Triple: [Santa Barbara Cemetery, hasNotableBurial, Thomas M. Storke]
Generated description
Thomas M. Storke was an American newspaper publisher and politician from Santa Barbara, California, known for his long-time leadership of the Santa Barbara News-Press and his influence on local and state politics.
Provenance (5 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_69f76e27758c81909b711cf38a130aaf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac2c58b88190a8bcae82724f781c |
completed | May 3, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a7c1ddfe90881909afd1403d78096ab |
completed | Aug. 12, 2026, 7:16 a.m. |
| NEDg | Description generation | batch_6a7c1e139f2081909d252f4055a7d3f5 |
completed | Aug. 12, 2026, 7:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a7c1ed117208190ac5352f8fb91fd92 |
completed | Aug. 12, 2026, 7:20 a.m. |
Created at: May 3, 2026, 4:07 p.m.