Triple
T33992980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L'Homme au doigt |
E871596
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object |
The Pointing Man
The Pointing Man is a famous bronze sculpture by Swiss artist Alberto Giacometti, renowned for its elongated, skeletal figure dramatically extending an outstretched arm.
|
E2077182
|
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: The Pointing Man | Statement: [L'Homme au doigt, title, The Pointing Man]
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: The Pointing Man Triple: [L'Homme au doigt, title, The Pointing Man]
Generated description
The Pointing Man is a famous bronze sculpture by Swiss artist Alberto Giacometti, renowned for its elongated, skeletal figure dramatically extending an outstretched arm.
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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f703c912c881908a4527060c3df66b |
completed | May 3, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3692e16034819090f920eb4f21f85e |
completed | June 20, 2026, 1:17 p.m. |
| NEDg | Description generation | batch_6a3693978aa881909be8384c3d62bc33 |
completed | June 20, 2026, 1:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3694bc096081909982b082aec3241d |
completed | June 20, 2026, 1:25 p.m. |
Created at: May 1, 2026, 1:50 a.m.