Triple
T14228239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcos |
E352679
|
entity |
| Predicate | isCognateOf |
P2527
|
FINISHED |
| Object |
Mark
Mark is a common given name of Latin origin, historically associated with the Gospel writer Mark the Evangelist and widely used in many English-speaking countries.
|
E161211
|
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: Mark | Statement: [Marcos, isCognateOf, Mark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Context triple: [Marcos, isCognateOf, Mark]
-
A.
Mark
The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
-
B.
Mark
Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
-
C.
Mark
Mark refers to the historic Margraviate of Brandenburg, a key principality of the Holy Roman Empire that later formed the core territory of Brandenburg-Prussia.
-
D.
Mark
Mark is a river in the southern Netherlands and northern Belgium that flows through the province of North Brabant before joining the Dintel.
-
E.
Mark
Mark is a punctuation symbol used in writing systems, including those that employ the Cyrillic Extended-B Unicode block.
- 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: Mark Triple: [Marcos, isCognateOf, Mark]
Generated description
Mark is a common given name of Latin origin, historically associated with the Gospel writer Mark the Evangelist and widely used in many English-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Target entity description: Mark is a common given name of Latin origin, historically associated with the Gospel writer Mark the Evangelist and widely used in many English-speaking countries.
-
A.
Mark
chosen
Mark is a common masculine given name of Latin origin, derived from Marcus and historically associated with figures such as the evangelist Saint Mark.
-
B.
Mark
Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
-
C.
Mark
Mark is one of the four canonical Gospels in the New Testament, traditionally attributed to John Mark and known for its concise, fast-paced account of the life, ministry, death, and resurrection of Jesus Christ.
-
D.
Mark
Mark is the given name of filmmaker Mark Neveldine, known for co-directing high-energy action films like the "Crank" series.
-
E.
Mark
Mark is the real first name of The Undertaker, the legendary professional wrestler best known for his long-running career in WWE.
- F. None of above.
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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622a48508190bbfedb762bd1674d |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3251ec5881909fcebc9477d6a761 |
completed | May 8, 2026, 12:46 a.m. |
| NEDg | Description generation | batch_69fd3408af2481909ff159694ed2d767 |
completed | May 8, 2026, 12:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3460d8e88190884e7d532645b79c |
completed | May 8, 2026, 12:54 a.m. |
Created at: April 10, 2026, 1:07 a.m.