Triple
T27303197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Porter |
E688973
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Heart of the Rockies
Heart of the Rockies is a 1951 American Western film featuring frontier adventure and law-and-order themes, in which actress Jean Porter appears in a notable role.
|
E1767711
|
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: Heart of the Rockies | Statement: [Jean Porter, notableWork, Heart of the Rockies]
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: Heart of the Rockies Triple: [Jean Porter, notableWork, Heart of the Rockies]
Generated description
Heart of the Rockies is a 1951 American Western film featuring frontier adventure and law-and-order themes, in which actress Jean Porter appears in a notable role.
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_69ef355b931c8190a63cafaf7bcc008b |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f627862bb8819091d51890051ddb97 |
completed | May 2, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a129cace7d8819089ab0ec258a0e176 |
completed | May 24, 2026, 6:37 a.m. |
| NEDg | Description generation | batch_6a129dc563e081909b6e07e29aad6ddb |
completed | May 24, 2026, 6:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a129e5f7e348190af4a279de8ef8caa |
completed | May 24, 2026, 6:44 a.m. |
Created at: April 27, 2026, 11:23 a.m.