Triple
T9255961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larsa |
E222443
|
entity |
| Predicate | hasTemple |
P1191
|
FINISHED |
| Object | E-babbar |
E351430
|
NE FINISHED |
How this triple was built (2 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: E-babbar | Statement: [Larsa, hasTemple, E-babbar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: E-babbar Context triple: [Larsa, hasTemple, E-babbar]
-
A.
Ebabbar
chosen
Ebabbar was the principal sun-god temple of the ancient Mesopotamian city of Sippar, dedicated to the deity Shamash.
-
B.
BABA
BABA is the stock ticker for Alibaba Group Holding Limited, a leading Chinese multinational technology company specializing in e-commerce, cloud computing, digital media, and related services.
-
C.
E-hulhul
E-hulhul was an ancient Mesopotamian temple dedicated to the moon god Sin, likely serving as an important religious center in his cult.
-
D.
Bandabi
Bandabi is the Asiatic black bear mascot of the PyeongChang 2018 Winter Paralympic Games, symbolizing courage and strong will.
-
E.
Inbam
Inbam is the third section of the ancient Tamil classic Tirukkural, focusing on love and the emotional aspects of human life.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b3c314819096632b8263288aae |
completed | April 1, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09bde36688190bf66669f585dcee7 |
completed | April 4, 2026, 5:04 a.m. |
Created at: March 30, 2026, 7:32 p.m.