Triple
T23973298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tam Coc caves |
E604292
|
entity |
| Predicate | hasViewpoint |
P854
|
FINISHED |
| Object |
Mua Cave viewpoint (nearby)
Mua Cave viewpoint is a popular scenic overlook in Ninh Binh, Vietnam, known for its steep stair climb leading to panoramic views of limestone karsts, rice fields, and the Tam Coc river valley.
|
E1613271
|
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: Mua Cave viewpoint (nearby) | Statement: [Tam Coc caves, hasViewpoint, Mua Cave viewpoint (nearby)]
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: Mua Cave viewpoint (nearby) Triple: [Tam Coc caves, hasViewpoint, Mua Cave viewpoint (nearby)]
Generated description
Mua Cave viewpoint is a popular scenic overlook in Ninh Binh, Vietnam, known for its steep stair climb leading to panoramic views of limestone karsts, rice fields, and the Tam Coc river valley.
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_69e29543019c8190872462e593cc50b4 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d1dda91c8190af716bceb3225aee |
completed | April 29, 2026, 9:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0f7e7b6d288190b3e963a2df042a48 |
completed | May 21, 2026, 9:51 p.m. |
| NEDg | Description generation | batch_6a0f7f6d3d0c8190a408c4dee4ac1f93 |
completed | May 21, 2026, 9:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0f803e39408190b612e1bade70bac2 |
completed | May 21, 2026, 9:59 p.m. |
Created at: April 17, 2026, 9:25 p.m.