Triple
T26597040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fearless-class patrol vessel |
E667516
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
RSS Fearless
RSS Fearless was the lead ship of the Republic of Singapore Navy’s Fearless-class patrol vessels, serving as a coastal patrol and anti-submarine warfare platform.
|
E1733158
|
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: RSS Fearless | Statement: [Fearless-class patrol vessel, namedAfter, RSS Fearless]
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: RSS Fearless Triple: [Fearless-class patrol vessel, namedAfter, RSS Fearless]
Generated description
RSS Fearless was the lead ship of the Republic of Singapore Navy’s Fearless-class patrol vessels, serving as a coastal patrol and anti-submarine warfare platform.
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_69ee9cfc385081909ac9ae178030a06e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f6152acd1c8190b2b357c93b2b3d3c |
completed | May 2, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11c83f3f288190aed2546950bc946e |
completed | May 23, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_6a11c91aa6888190b17f656a39eefd1e |
completed | May 23, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11ca68b0488190851b0634a0c784bd |
completed | May 23, 2026, 3:40 p.m. |
Created at: April 27, 2026, 2:10 a.m.