Triple
T25776565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port San Luis Harbor |
E649165
|
entity |
| Predicate | hasBodyOfWater |
P1778
|
FINISHED |
| Object |
San Luis Obispo Bay
San Luis Obispo Bay is a coastal embayment on California’s central coast known for its sheltered waters, marine life, and recreational boating and fishing.
|
E1697929
|
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: San Luis Obispo Bay | Statement: [Port San Luis Harbor, hasBodyOfWater, San Luis Obispo Bay]
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: San Luis Obispo Bay Triple: [Port San Luis Harbor, hasBodyOfWater, San Luis Obispo Bay]
Generated description
San Luis Obispo Bay is a coastal embayment on California’s central coast known for its sheltered waters, marine life, and recreational boating and fishing.
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_69e7ab333b508190b6d708d8d9a328ed |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fe5c90dc8190910ea0d8f7f35cd7 |
completed | May 2, 2026, 1:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10da0d004481909c8bc88b86126684 |
completed | May 22, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_6a10db36562c8190823f00ae5794c05d |
completed | May 22, 2026, 10:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10dc2096b881909e87c9cc277bc831 |
completed | May 22, 2026, 10:43 p.m. |
Created at: April 22, 2026, 5:34 a.m.