Triple
T3278260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etemenanki |
E68809
|
entity |
| Predicate | mentionedBy |
P831
|
FINISHED |
| Object |
Berosus
Berosus was a Hellenistic-era Babylonian priest and historian known for writing a Greek-language history of Babylonia that preserved Mesopotamian myths, traditions, and astronomical knowledge.
|
E344843
|
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: Berosus | Statement: [Etemenanki, mentionedBy, Berosus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berosus Context triple: [Etemenanki, mentionedBy, Berosus]
-
A.
Maurus
Maurus is a masculine given name of Latin origin, historically associated with early Christian saints and used as a variant of names like Maurice.
-
B.
Orlybus
Orlybus is a dedicated airport shuttle bus service connecting central Paris with Orly Airport.
-
C.
Hyas
Hyas is a figure in Greek mythology, often associated with the Hyades as their brother and linked to myths explaining the origin of certain constellations or rain-bringing stars.
-
D.
Critobulus
Critobulus was an ancient Athenian known from Plato’s dialogues as the son of Crito and an associate of Socrates.
-
E.
Ambrysus
Ambrysus was an ancient Greek city in the region of Phocis, known for its strategic location and role in classical Greek history.
- 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: Berosus Triple: [Etemenanki, mentionedBy, Berosus]
Generated description
Berosus was a Hellenistic-era Babylonian priest and historian known for writing a Greek-language history of Babylonia that preserved Mesopotamian myths, traditions, and astronomical knowledge.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Berosus Target entity description: Berosus was a Hellenistic-era Babylonian priest and historian known for writing a Greek-language history of Babylonia that preserved Mesopotamian myths, traditions, and astronomical knowledge.
-
A.
Maurus
Maurus is a masculine given name of Latin origin, historically associated with early Christian saints and used as a variant of names like Maurice.
-
B.
Orlybus
Orlybus is a dedicated airport shuttle bus service connecting central Paris with Orly Airport.
-
C.
Hyas
Hyas is a figure in Greek mythology, often associated with the Hyades as their brother and linked to myths explaining the origin of certain constellations or rain-bringing stars.
-
D.
Critobulus
Critobulus was an ancient Athenian known from Plato’s dialogues as the son of Crito and an associate of Socrates.
-
E.
Ambrysus
Ambrysus was an ancient Greek city in the region of Phocis, known for its strategic location and role in classical Greek history.
- 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_69ad859c463481909ca4be267336c290 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb013de048190bcaac732caa6b174 |
completed | March 8, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e84ddd24819094a47269023f9889 |
completed | March 12, 2026, 4:22 p.m. |
| NEDg | Description generation | batch_69b2e8d04e508190916455fa2f4702b5 |
completed | March 12, 2026, 4:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2ed0f862c81909d9a279bea549339 |
completed | March 12, 2026, 4:42 p.m. |
Created at: March 8, 2026, 3:10 p.m.