Triple
T36659836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paciano Rizal |
E905089
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object |
Olympia Rizal
Olympia Rizal was one of the elder sisters of Philippine national hero José Rizal, belonging to the prominent Rizal family of 19th-century Calamba.
|
E2194920
|
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: Olympia Rizal | Statement: [Paciano Rizal, sibling, Olympia Rizal]
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: Olympia Rizal Triple: [Paciano Rizal, sibling, Olympia Rizal]
Generated description
Olympia Rizal was one of the elder sisters of Philippine national hero José Rizal, belonging to the prominent Rizal family of 19th-century Calamba.
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_69f76e6e3b908190970251b30f76ad71 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c77b118881908cad488643e61e8a |
completed | May 3, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3a381668348190bfb9fed761ae1dc7 |
completed | June 23, 2026, 7:39 a.m. |
| NEDg | Description generation | batch_6a3a38b8c23c819099237e0df0773c5e |
completed | June 23, 2026, 7:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3a39b713148190975bd3ea6829ffd5 |
completed | June 23, 2026, 7:45 a.m. |
Created at: May 3, 2026, 4:11 p.m.