Triple
T15758813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amorite dynasty of Mari |
E382038
|
entity |
| Predicate | sourceOfKnowledge |
P4092
|
FINISHED |
| Object |
Mari archives
The Mari archives are a vast collection of cuneiform tablets from the ancient city of Mari that provide crucial insights into the political, economic, and social life of the Amorite period in Mesopotamia.
|
E1175154
|
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: Mari archives | Statement: [Amorite dynasty of Mari, sourceOfKnowledge, Mari archives]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mari archives Context triple: [Amorite dynasty of Mari, sourceOfKnowledge, Mari archives]
-
A.
MAR
MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
-
B.
MAR
MAR is the stock ticker symbol for Marriott International, a leading global hotel and lodging company.
-
C.
Marg
Marg is a given name, typically a shortened form of Margaret, used primarily in English-speaking contexts.
-
D.
Mari
Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
-
E.
Mari
Mari is the central character of the film "Return to Sender," around whom the story’s psychological drama and suspense unfold.
- 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: Mari archives Triple: [Amorite dynasty of Mari, sourceOfKnowledge, Mari archives]
Generated description
The Mari archives are a vast collection of cuneiform tablets from the ancient city of Mari that provide crucial insights into the political, economic, and social life of the Amorite period in Mesopotamia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mari archives Target entity description: The Mari archives are a vast collection of cuneiform tablets from the ancient city of Mari that provide crucial insights into the political, economic, and social life of the Amorite period in Mesopotamia.
-
A.
MAR
MAR is the three-letter ISO 3166-1 alpha-3 country code assigned to Morocco.
-
B.
MAR
MAR is the stock ticker symbol for Marriott International, a leading global hotel and lodging company.
-
C.
Marg
Marg is a given name, typically a shortened form of Margaret, used primarily in English-speaking contexts.
-
D.
Mari
Mari is a character in Paulo Coelho's novel "Veronika Decides to Die," portrayed as a fellow patient in the mental institution who struggles with anxiety and societal expectations.
-
E.
Mari
Mari is the central character of the film "Return to Sender," around whom the story’s psychological drama and suspense unfold.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b35ea48190a758ee76a57b5451 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8774eda08190a6231b4fd5027e6f |
completed | May 9, 2026, 7:13 p.m. |
| NEDg | Description generation | batch_69ff885d33708190adb157afa7dc2e07 |
completed | May 9, 2026, 7:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff8948cc68819085c3953226236394 |
completed | May 9, 2026, 7:21 p.m. |
Created at: April 10, 2026, 4:47 a.m.