Triple
T16948564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dok |
E411126
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Docus
Docus is an alternative name for Dok, likely referring to the same entity, brand, or product under a different designation.
|
E1241646
|
NE FINISHED |
How this triple was built (4 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: Docus | Statement: [Dok, hasAlternativeName, Docus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Docus Context triple: [Dok, hasAlternativeName, Docus]
-
A.
DOCU
DOCU is the stock ticker symbol for DocuSign, a leading provider of electronic signature and digital agreement management solutions.
-
B.
DOCO
DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
-
C.
DOC
DOC is the commonly used abbreviation for the Division of Organic Chemistry, a professional organization focused on advancing research and education in organic chemistry.
-
D.
DOC
DOC is the commonly used abbreviation for the New York City Department of Correction, the agency responsible for operating the city’s jail system.
-
E.
DOC
DOC (Denominação de Origem Controlada) is Portugal’s highest wine classification, designating wines from strictly regulated and geographically defined regions known for their quality and typicity.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Docus Triple: [Dok, hasAlternativeName, Docus]
Generated description
Docus is an alternative name for Dok, likely referring to the same entity, brand, or product under a different designation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Docus Target entity description: Docus is an alternative name for Dok, likely referring to the same entity, brand, or product under a different designation.
-
A.
DOCU
DOCU is the stock ticker symbol for DocuSign, a leading provider of electronic signature and digital agreement management solutions.
-
B.
DOCO
DOCO is a mixed-use entertainment, shopping, and dining district in downtown Sacramento, California, adjacent to the Golden 1 Center.
-
C.
DOC
DOC is the commonly used abbreviation for the Division of Organic Chemistry, a professional organization focused on advancing research and education in organic chemistry.
-
D.
DOC
DOC is the commonly used abbreviation for the New York City Department of Correction, the agency responsible for operating the city’s jail system.
-
E.
DOC
DOC (Denominação de Origem Controlada) is Portugal’s highest wine classification, designating wines from strictly regulated and geographically defined regions known for their quality and typicity.
- F. None of above. chosen
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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfb4b1b08190b608d36a209ed6bd |
completed | April 18, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfeeee948190a5c8904d1f559a28 |
completed | May 10, 2026, 6:35 p.m. |
| NEDg | Description generation | batch_6a00d0c0ecc48190b88dcb170926bf16 |
completed | May 10, 2026, 6:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d194e9e08190bf0c4c0fe3921978 |
completed | May 10, 2026, 6:42 p.m. |
Created at: April 10, 2026, 5:31 a.m.