Triple
T9990107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yam |
E196863
|
entity |
| Predicate | paralleledBy |
P278
|
FINISHED |
| Object |
Lotan
Lotan is a multi-headed sea serpent or dragon from ancient Northwest Semitic mythology, often associated with chaos and defeated by the storm god.
|
E834359
|
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: Lotan | Statement: [Yam, paralleledBy, Lotan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lotan Context triple: [Yam, paralleledBy, Lotan]
-
A.
Lotso
Lotso is the strawberry-scented teddy bear who serves as the main antagonist in Pixar's animated film Toy Story 3.
-
B.
Lotha
Lotha is a Naga ethnic group primarily inhabiting the Wokha district of Nagaland in Northeast India, known for its rich cultural traditions and festivals.
-
C.
Lusei
Lusei are a major clan of the Mizo people of Northeast India, historically influential in shaping Mizo culture, language, and social organization.
-
D.
The Turim
The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
-
E.
Lakitu
Lakitu is a recurring cloud-riding Koopa in the Super Mario series known for hovering above the player and attacking by throwing Spiny eggs.
- 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: Lotan Triple: [Yam, paralleledBy, Lotan]
Generated description
Lotan is a multi-headed sea serpent or dragon from ancient Northwest Semitic mythology, often associated with chaos and defeated by the storm god.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lotan Target entity description: Lotan is a multi-headed sea serpent or dragon from ancient Northwest Semitic mythology, often associated with chaos and defeated by the storm god.
-
A.
Lotso
Lotso is the strawberry-scented teddy bear who serves as the main antagonist in Pixar's animated film Toy Story 3.
-
B.
Lotha
Lotha is a Naga ethnic group primarily inhabiting the Wokha district of Nagaland in Northeast India, known for its rich cultural traditions and festivals.
-
C.
Lusei
Lusei are a major clan of the Mizo people of Northeast India, historically influential in shaping Mizo culture, language, and social organization.
-
D.
The Turim
The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
-
E.
Lakitu
Lakitu is a recurring cloud-riding Koopa in the Super Mario series known for hovering above the player and attacking by throwing Spiny eggs.
- 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_69ca82f1678c819093d06320a05f16a4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdc7a0cb6481908d7bd1b43f93bd18 |
completed | April 2, 2026, 1:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d258190f408190949d50badb3ec6f9 |
completed | April 5, 2026, 12:39 p.m. |
| NEDg | Description generation | batch_69d2599e85e88190aad263e8ba169275 |
completed | April 5, 2026, 12:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d25a0cb08481909003b5bdab5c834b |
completed | April 5, 2026, 12:48 p.m. |
Created at: March 30, 2026, 8:50 p.m.